Topic Keywords

[ $\ell_1$ norm ] [ $f-$divergence ] [ 3D Convolution ] [ 3D deep learning ] [ 3D generation ] [ 3d point cloud ] [ 3D Reconstruction ] [ 3D scene understanding ] [ 3D shape representations ] [ 3D shapes learning ] [ 3D vision ] [ 3D Vision ] [ abstract reasoning ] [ abstract rules ] [ Acceleration ] [ accuracy ] [ acoustic condition modeling ] [ Action localization ] [ action recognition ] [ activation maximization ] [ activation strategy. ] [ Active learning ] [ Active Learning ] [ AdaBoost ] [ adaptive heavy-ball methods ] [ Adaptive Learning ] [ adaptive methods ] [ adaptive optimization ] [ ADMM ] [ Adversarial Accuracy ] [ Adversarial Attack ] [ Adversarial Attacks ] [ adversarial attacks/defenses ] [ Adversarial computer programs ] [ Adversarial Defense ] [ Adversarial Example Detection ] [ Adversarial Examples ] [ Adversarial Learning ] [ Adversarial Machine Learning ] [ adversarial patch ] [ Adversarial robustness ] [ Adversarial Robustness ] [ Adversarial training ] [ Adversarial Training ] [ Adversarial Transferability ] [ aesthetic assessment ] [ affine parameters ] [ age estimation ] [ Aggregation Methods ] [ AI for earth science ] [ ALFRED ] [ Algorithm ] [ algorithmic fairness ] [ Algorithmic fairness ] [ Algorithms ] [ alignment ] [ alignment of semantic and visual space ] [ amortized inference ] [ Analogies ] [ annotation artifacts ] [ anomaly-detection ] [ Anomaly detection with deep neural networks ] [ anonymous walk ] [ appearance transfer ] [ approximate constrained optimization ] [ approximation ] [ Approximation ] [ Architectures ] [ argoverse ] [ Artificial Integlligence ] [ ASR ] [ assistive technology ] [ associative memory ] [ Associative Memory ] [ asynchronous parallel algorithm ] [ Atari ] [ Attention ] [ Attention Mechanism ] [ Attention Modules ] [ attractors ] [ attributed walks ] [ Auction Theory ] [ audio understanding ] [ Audio-Visual ] [ audio visual learning ] [ audio-visual representation ] [ audio-visual representation learning ] [ Audio-visual sound separation ] [ audiovisual synthesis ] [ augmented deep reinforcement learning ] [ autodiff ] [ Autoencoders ] [ automated data augmentation ] [ automated machine learning ] [ automatic differentiation ] [ AutoML ] [ autonomous learning ] [ autoregressive language model ] [ Autoregressive Models ] [ AutoRL ] [ auxiliary information ] [ auxiliary latent variable ] [ Auxiliary Learning ] [ auxiliary task ] [ Average-case Analysis ] [ aversarial examples ] [ avoid knowledge leaking ] [ backdoor attack ] [ Backdoor Attacks ] [ Backdoor Defense ] [ Backgrounds ] [ backprop ] [ back translation ] [ backward error analysis ] [ bagging ] [ batchnorm ] [ Batch Normalization ] [ batch reinforcement learning ] [ Batch Reinforcement Learning ] [ batch selection ] [ Bayesian ] [ Bayesian classification ] [ Bayesian inference ] [ Bayesian Inference ] [ Bayesian networks ] [ Bayesian Neural Networks ] [ behavior cloning ] [ belief-propagation ] [ Benchmark ] [ benchmarks ] [ benign overfitting ] [ bert ] [ BERT ] [ beta-VAE ] [ better generalization ] [ biased sampling ] [ biases ] [ Bias in Language Models ] [ bidirectional ] [ bilevel optimization ] [ Bilinear games ] [ Binary Embeddings ] [ Binary Neural Networks ] [ binaural audio ] [ binaural speech ] [ biologically plausible ] [ Biometrics ] [ bisimulation ] [ Bisimulation ] [ bisimulation metrics ] [ bit-flip ] [ bit-level sparsity ] [ blind denoising ] [ blind spots ] [ block mdp ] [ boosting ] [ bottleneck ] [ bptt ] [ branch and bound ] [ Brownian motion ] [ Budget-Aware Pruning ] [ Budget constraints ] [ Byzantine resilience ] [ Byzantine SGD ] [ CAD modeling ] [ calibration ] [ Calibration ] [ calibration measure ] [ cancer research ] [ Capsule Networks ] [ Catastrophic forgetting ] [ Catastrophic Forgetting ] [ Causal Inference ] [ Causality ] [ Causal network ] [ certificate ] [ certified defense ] [ Certified Robustness ] [ challenge sets ] [ change of measure ] [ change point detection ] [ channel suppressing ] [ Channel Tensorization ] [ Channel-Wise Approximated Activation ] [ Chaos ] [ chebyshev polynomial ] [ checkpointing ] [ Checkpointing ] [ chemistry ] [ CIFAR ] [ Classification ] [ class imbalance ] [ clean-label ] [ Clustering ] [ Clusters ] [ CNN ] [ CNNs ] [ Code Compilation ] [ Code Representations ] [ Code Structure ] [ code summarization ] [ Code Summarization ] [ Cognitively-inspired Learning ] [ cold posteriors ] [ collaborative learning ] [ Combinatorial optimization ] [ common object counting ] [ commonsense question answering ] [ Commonsense Reasoning ] [ Communication Compression ] [ co-modulation ] [ complete verifiers ] [ complex query answering ] [ Composition ] [ compositional generalization ] [ compositional learning ] [ compositional task ] [ Compressed videos ] [ Compressing Deep Networks ] [ Compression ] [ computation ] [ computational biology ] [ Computational Biology ] [ computational complexity ] [ Computational imaging ] [ Computational neuroscience ] [ Computational resources ] [ computer graphics ] [ Computer Vision ] [ concentration ] [ Concentration of Measure ] [ Concept-based Explanation ] [ concept drift ] [ Concept Learning ] [ conditional expectation ] [ Conditional GANs ] [ Conditional Generation ] [ Conditional generative adversarial networks ] [ conditional layer normalization ] [ Conditional Neural Processes ] [ Conditional Risk Minimization ] [ Conditional Sampling ] [ conditional text generation ] [ Conferrability ] [ confidentiality ] [ conformal inference ] [ conformal prediction ] [ conjugacy ] [ conservation law ] [ consistency ] [ consistency training ] [ Consistency Training ] [ constellation models ] [ constrained beam search ] [ Constrained optimization ] [ constrained RL ] [ constraints ] [ constraint satisfaction ] [ contact tracing ] [ Contextual Bandits ] [ Contextual embedding space ] [ Continual learning ] [ Continual Learning ] [ continuation method ] [ continuous and scalar conditions ] [ continuous case ] [ Continuous Control ] [ continuous convolution ] [ continuous games ] [ continuous normalizing flow ] [ continuous time ] [ Continuous-time System ] [ continuous treatment effect ] [ contrastive divergence ] [ Contrastive learning ] [ Contrastive Learning ] [ Contrastive Methods ] [ contrastive representation learning ] [ control barrier function ] [ controlled generation ] [ Controlled NLG ] [ Convergence ] [ Convergence Analysis ] [ convex duality ] [ Convex optimization ] [ ConvNets ] [ convolutional kernel methods ] [ Convolutional Layer ] [ convolutional models ] [ Convolutional Networks ] [ copositive programming ] [ corruptions ] [ COST ] [ Counterfactual inference ] [ counterfactuals ] [ Counterfactuals ] [ covariant neural networks ] [ covid-19 ] [ COVID-19 ] [ Cross-domain ] [ cross-domain few-shot learning ] [ cross-domain video generation ] [ cross-episode attention ] [ cross-fitting ] [ cross-lingual pretraining ] [ Cryptographic inference ] [ cultural transmission ] [ Curriculum Learning ] [ curse of memory ] [ curvature estimates ] [ custom voice ] [ cycle-consistency regularization ] [ cycle-consistency regularizer ] [ DAG ] [ DARTS stability ] [ Data augmentation ] [ Data Augmentation ] [ data cleansing ] [ Data-driven modeling ] [ data-efficient learning ] [ data-efficient RL ] [ Data Flow ] [ data labeling ] [ data parallelism ] [ Data Poisoning ] [ Data Protection ] [ Dataset ] [ dataset bias ] [ dataset compression ] [ dataset condensation ] [ dataset corruption ] [ dataset distillation ] [ dataset summarization ] [ data structures ] [ debiased training ] [ debugging ] [ Decentralized Optimization ] [ decision boundary geometry ] [ decision trees ] [ declarative knowledge ] [ deep-anomaly-detection ] [ Deep Architectures ] [ Deep denoising priors ] [ deep embedding ] [ Deep Ensembles ] [ deep equilibrium models ] [ Deep Equilibrium Models ] [ Deepfake ] [ deep FBSDEs ] [ Deep Gaussian Processes ] [ Deep generative model ] [ Deep generative modeling ] [ Deep generative models ] [ deeplearning ] [ Deep learning ] [ Deep Learning ] [ deep learning dynamics ] [ Deep Learning Theory ] [ deep network training ] [ deep neural network ] [ deep neural networks. ] [ Deep Neural Networks ] [ deep one-class classification ] [ deep Q-learning ] [ Deep reinforcement learning ] [ Deep Reinforcement Learning ] [ deep ReLU networks ] [ Deep residual neural networks ] [ deep RL ] [ deep sequence model ] [ deepset ] [ Deep Sets ] [ Deformation Modeling ] [ delay ] [ Delay differential equations ] [ denoising score matching ] [ Dense Retrieval ] [ Density estimation ] [ Density Estimation ] [ Density ratio estimation ] [ dependency based method ] [ deployment-efficiency ] [ depression ] [ depth separation ] [ descent ] [ description length ] [ determinantal point processes ] [ Device Placement ] [ dialogue state tracking ] [ differentiable optimization ] [ Differentiable physics ] [ Differentiable Physics ] [ Differentiable program generator ] [ differentiable programming ] [ Differentiable rendering ] [ Differentiable simulation ] [ differential dynamica programming ] [ differential equations ] [ Differential Geometry ] [ differentially private deep learning ] [ Differential Privacy ] [ diffusion probabilistic models ] [ diffusion process ] [ dimension ] [ Directed Acyclic Graphs ] [ Dirichlet form ] [ Discrete Optimization ] [ discretization error ] [ disentangled representation learning ] [ Disentangled representation learning ] [ Disentanglement ] [ distance ] [ Distillation ] [ distinct elements ] [ Distributed ] [ distributed deep learning ] [ distributed inference ] [ Distributed learning ] [ distributed machine learning ] [ Distributed ML ] [ Distributed Optimization ] [ distributional robust optimization ] [ distribution estimation ] [ distribution shift ] [ diverse strategies ] [ diverse video generation ] [ Diversity denoising ] [ Diversity Regularization ] [ DNN ] [ DNN compression ] [ document analysis ] [ document classification ] [ document retrieval ] [ domain adaptation theory ] [ Domain Adaption ] [ Domain Generalization ] [ domain randomization ] [ Domain Translation ] [ double descent ] [ Double Descent ] [ doubly robustness ] [ Doubly-weighted Laplace operator ] [ Dropout ] [ drug discovery ] [ Drug discovery ] [ dst ] [ Dual-mode ASR ] [ Dueling structure ] [ Dynamical Systems ] [ dynamic computation graphs ] [ dynamics ] [ dynamics prediction ] [ dynamic systems ] [ Early classification ] [ Early pruning ] [ early stopping ] [ EBM ] [ Edit ] [ EEG ] [ effective learning rate ] [ Efficiency ] [ Efficient Attention Mechanism ] [ efficient deep learning ] [ Efficient Deep Learning ] [ Efficient Deep Learning Inference ] [ Efficient ensembles ] [ efficient inference ] [ efficient inference methods ] [ Efficient Inference Methods ] [ EfficientNets ] [ efficient network ] [ Efficient Networks ] [ Efficient training ] [ Efficient Training ] [ efficient training and inference. ] [ egocentric ] [ eigendecomposition ] [ Eigenspectrum ] [ ELBO ] [ electroencephalography ] [ EM ] [ Embedding Models ] [ Embedding Size ] [ Embodied Agents ] [ embodied vision ] [ emergent behavior ] [ empirical analysis ] [ Empirical Game Theory ] [ empirical investigation ] [ Empirical Investigation ] [ empirical study ] [ empowerment ] [ Encoder layer fusion ] [ end-to-end entity linking ] [ End-to-End Object Detection ] [ Energy ] [ Energy-Based GANs ] [ energy based model ] [ energy-based model ] [ Energy-based model ] [ energy based models ] [ Energy-based Models ] [ Energy Based Models ] [ Energy-Based Models ] [ Energy Score ] [ ensemble ] [ Ensemble ] [ ensemble learning ] [ ensembles ] [ Ensembles ] [ entity disambiguation ] [ entity linking ] [ entity retrieval ] [ entropic algorithms ] [ Entropy Maximization ] [ Entropy Model ] [ entropy regularization ] [ epidemiology ] [ episode-level pretext task ] [ episodic training ] [ equilibrium ] [ equivariant ] [ equivariant neural network ] [ ERP ] [ Evaluation ] [ evaluation of interpretability ] [ Event localization ] [ evolution ] [ Evolutionary algorithm ] [ Evolutionary Algorithm ] [ Evolutionary Algorithms ] [ Excess risk ] [ experience replay buffer ] [ experimental evaluation ] [ Expert Models ] [ Explainability ] [ explainable ] [ Explainable AI ] [ Explainable Model ] [ explaining decision-making ] [ explanation method ] [ explanations ] [ Explanations ] [ Exploration ] [ Exponential Families ] [ exponential tilting ] [ exposition ] [ external memory ] [ Extrapolation ] [ extremal sector ] [ facial recognition ] [ factor analysis ] [ factored MDP ] [ Factored MDP ] [ fairness ] [ Fairness ] [ faithfulness ] [ fast DNN inference ] [ fast learning rate ] [ fast-mapping ] [ fast weights ] [ FAVOR ] [ Feature Attribution ] [ feature propagation ] [ features ] [ feature visualization ] [ Feature Visualization ] [ Federated learning ] [ Federated Learning ] [ Few Shot ] [ few-shot concept learning ] [ few-shot domain generalization ] [ Few-shot learning ] [ Few Shot Learning ] [ fine-tuning ] [ finetuning ] [ Fine-tuning ] [ Finetuning ] [ fine-tuning stability ] [ Fingerprinting ] [ First-order Methods ] [ first-order optimization ] [ fisher ratio ] [ flat minima ] [ Flexibility ] [ flow graphs ] [ Fluid Dynamics ] [ Follow-the-Regularized-Leader ] [ Formal Verification ] [ forward mode ] [ Fourier Features ] [ Fourier transform ] [ framework ] [ Frobenius norm ] [ from-scratch ] [ frontend ] [ fruit fly ] [ fully-connected ] [ Fully-Connected Networks ] [ future frame generation ] [ future link prediction ] [ fuzzy tiling activation function ] [ Game Decomposition ] [ Game Theory ] [ GAN ] [ GAN compression ] [ GANs ] [ Garbled Circuits ] [ Gaussian Copula ] [ Gaussian Graphical Model ] [ Gaussian Isoperimetric Inequality ] [ Gaussian mixture model ] [ Gaussian process ] [ Gaussian Process ] [ Gaussian Processes ] [ gaussian process priors ] [ GBDT ] [ generalisation ] [ Generalization ] [ Generalization Bounds ] [ generalization error ] [ Generalization Measure ] [ Generalization of Reinforcement Learning ] [ generalized ] [ generalized Girsanov theorem ] [ Generalized PageRank ] [ Generalized zero-shot learning ] [ Generation ] [ Generative Adversarial Network ] [ Generative Adversarial Networks ] [ generative art ] [ Generative Flow ] [ Generative Model ] [ Generative modeling ] [ Generative Modeling ] [ generative modelling ] [ Generative Modelling ] [ Generative models ] [ Generative Models ] [ genetic programming ] [ Geodesic-Aware FC Layer ] [ geometric ] [ Geometric Deep Learning ] [ G-invariance regularization ] [ global ] [ global optima ] [ Global Reference ] [ glue ] [ GNN ] [ GNNs ] [ goal-conditioned reinforcement learning ] [ goal-conditioned RL ] [ goal reaching ] [ gradient ] [ gradient alignment ] [ Gradient Alignment ] [ gradient boosted decision trees ] [ gradient boosting ] [ gradient decomposition ] [ Gradient Descent ] [ gradient descent-ascent ] [ gradient flow ] [ Gradient flow ] [ gradient flows ] [ gradient redundancy ] [ Gradient stability ] [ Grammatical error correction ] [ Granger causality ] [ Graph ] [ graph classification ] [ graph coarsening ] [ Graph Convolutional Network ] [ Graph Convolutional Neural Networks ] [ graph edit distance ] [ Graph Generation ] [ Graph Generative Model ] [ graph-level prediction ] [ graph networks ] [ Graph neural network ] [ Graph Neural Network ] [ Graph neural networks ] [ Graph Neural Networks ] [ Graph pooling ] [ graph representation learning ] [ Graph representation learning ] [ Graph Representation Learning ] [ graph shift operators ] [ graph-structured data ] [ graph structure learning ] [ Greedy Learning ] [ grid cells ] [ grounding ] [ group disparities ] [ group equivariance ] [ Group Equivariance ] [ Group Equivariant Convolution ] [ group equivariant self-attention ] [ group equivariant transformers ] [ group sparsity ] [ Group-supervised learning ] [ gumbel-softmax ] [ Hamiltonian systems ] [ hard-label attack ] [ hard negative mining ] [ hard negative sampling ] [ Hardware-Aware Neural Architecture Search ] [ Harmonic Analysis ] [ harmonic distortion analysis ] [ healthcare ] [ Healthcare ] [ heap allocation ] [ Hessian matrix ] [ Heterogeneity ] [ Heterogeneous ] [ heterogeneous data ] [ Heterogeneous data ] [ Heterophily ] [ heteroscedasticity ] [ heuristic search ] [ hidden-parameter mdp ] [ hierarchical contrastive learning ] [ Hierarchical Imitation Learning ] [ Hierarchical Multi-Agent Learning ] [ Hierarchical Networks ] [ Hierarchical Reinforcement Learning ] [ Hierarchy-Aware Classification ] [ high-dimensional asymptotics ] [ high-dimensional statistic ] [ high-resolution video generation ] [ hindsight relabeling ] [ histogram binning ] [ historical color image classification ] [ HMC ] [ homomorphic encryption ] [ Homophily ] [ Hopfield layer ] [ Hopfield networks ] [ Hopfield Networks ] [ human-AI collaboration ] [ human cognition ] [ human-computer interaction ] [ human preferences ] [ human psychophysics ] [ humans in the loop ] [ hybrid systems ] [ Hyperbolic ] [ hyperbolic deep learning ] [ Hyperbolic Geometry ] [ hypercomplex representation learning ] [ hypergradients ] [ Hypernetworks ] [ hyperparameter ] [ Hyperparameter Optimization ] [ Hyper-Parameter Optimization ] [ HYPERPARAMETER OPTIMIZATION ] [ Image Classification ] [ image completion ] [ Image compression ] [ Image Editing ] [ Image Generation ] [ Image manipulation ] [ Image Modeling ] [ ImageNet ] [ image reconstruction ] [ Image segmentation ] [ Image Synthesis ] [ image-to-action learning ] [ Image-to-Image Translation ] [ image translation ] [ image warping ] [ imbalanced learning ] [ Imitation Learning ] [ Impartial Learning ] [ implicit bias ] [ Implicit Bias ] [ Implicit Deep Learning ] [ implicit differentiation ] [ implicit functions ] [ implicit neural representations ] [ Implicit Neural Representations ] [ Implicit Representation ] [ Importance Weighting ] [ impossibility ] [ incoherence ] [ Incompatible Environments ] [ Incremental Tree Transformations ] [ independent component analysis ] [ indirection ] [ Individual mediation effects ] [ Inductive Bias ] [ inductive biases ] [ inductive representation learning ] [ infinitely wide neural network ] [ Infinite-Width Limit ] [ infinite-width networks ] [ influence functions ] [ Influence Functions ] [ Information bottleneck ] [ Information Bottleneck ] [ Information Geometry ] [ information-theoretical probing ] [ Information theory ] [ Information Theory ] [ Initialization ] [ input-adaptive multi-exit neural networks ] [ input convex neural networks ] [ input-convex neural networks ] [ InstaHide ] [ Instance adaptation ] [ instance-based label noise ] [ Instance learning ] [ Instance-wise Learning ] [ Instrumental Variable Regression ] [ integral probability metric ] [ intention ] [ interaction networks ] [ Interactions ] [ interactive fiction ] [ Internet of Things ] [ Interpolation Peak ] [ Interpretability ] [ interpretable latent representation ] [ Interpretable Machine Learning ] [ interpretable policy learning ] [ in-the-wild data ] [ Intrinsically Motivated Reinforcement Learning ] [ Intrinsic Motivation ] [ intrinsic motivations ] [ Intrinsic Reward ] [ Invariance and Equivariance ] [ invariance penalty ] [ invariances ] [ Invariant and equivariant deep networks ] [ Invariant Representations ] [ invariant risk minimization ] [ Invariant subspaces ] [ inverse graphics ] [ Inverse reinforcement learning ] [ Inverse Reinforcement Learning ] [ Inverted Index ] [ irl ] [ IRM ] [ irregularly spaced time series ] [ irregular-observed data modelling ] [ isometric ] [ Isotropy ] [ iterated learning ] [ iterative training ] [ JEM ] [ Johnson-Lindenstrauss Transforms ] [ kernel ] [ Kernel Learning ] [ kernel method ] [ kernel-ridge regression ] [ kernels ] [ keypoint localization ] [ Knowledge distillation ] [ Knowledge Distillation ] [ Knowledge factorization ] [ Knowledge Graph Reasoning ] [ knowledge uncertainty ] [ Kullback-Leibler divergence ] [ Kurdyka-Łojasiewicz geometry ] [ label noise robustness ] [ Label Representation ] [ Label shift ] [ label smoothing ] [ Langevin dynamics ] [ Langevin sampling ] [ Language Grounding ] [ Language Model ] [ Language modeling ] [ Language Modeling ] [ Language Modelling ] [ Language Model Pre-training ] [ language processing ] [ language-specific modeling ] [ Laplace kernel ] [ Large-scale ] [ Large-scale Deep Learning ] [ large scale learning ] [ Large-scale Machine Learning ] [ large-scale pre-trained language models ] [ large-scale training ] [ large vocabularies ] [ Last-iterate Convergence ] [ Latency-aware Neural Architecture Search ] [ Latent Simplex ] [ latent space of GANs ] [ Latent Variable Models ] [ lattices ] [ Layer order ] [ layerwise sparsity ] [ learnable ] [ learned algorithms ] [ Learned compression ] [ learned ISTA ] [ Learning ] [ learning action representations ] [ learning-based ] [ learning dynamics ] [ Learning Dynamics ] [ Learning in Games ] [ learning mechanisms ] [ Learning physical laws ] [ Learning Theory ] [ Learning to Hash ] [ learning to optimize ] [ Learning to Optimize ] [ learning to rank ] [ Learning to Rank ] [ learning to teach ] [ learning with noisy labels ] [ Learning with noisy labels ] [ library ] [ lifelong ] [ Lifelong learning ] [ Lifelong Learning ] [ lifted inference ] [ likelihood-based models ] [ likelihood-free inference ] [ limitations ] [ limited data ] [ linear bandits ] [ Linear Convergence ] [ linear estimator ] [ Linear Regression ] [ linear terms ] [ linformer ] [ Lipschitz constants ] [ Lipschitz constrained networks ] [ Local Explanations ] [ locality sensitive hashing ] [ Locally supervised training ] [ local Rademacher complexity ] [ log-concavity ] [ Logic ] [ Logic Rules ] [ logsignature ] [ Long-Tailed Recognition ] [ long-tail learning ] [ Long-term dependencies ] [ long-term prediction ] [ long-term stability ] [ loss correction ] [ Loss function search ] [ Loss Function Search ] [ lossless source compression ] [ Lottery Ticket ] [ Lottery Ticket Hypothesis ] [ lottery tickets ] [ low-dimensional structure ] [ lower bound ] [ lower bounds ] [ Low-latency ASR ] [ low precision training ] [ low rank ] [ low-rank approximation ] [ low-rank tensors ] [ L-smoothness ] [ LSTM ] [ Lyapunov Chaos ] [ Machine learning ] [ Machine Learning ] [ machine learning for code ] [ Machine Learning for Robotics ] [ Machine Learning (ML) for Programming Languages (PL)/Software Engineering (SE) ] [ machine learning systems ] [ Machine translation ] [ Machine Translation ] [ magnitude-based pruning ] [ Manifold clustering ] [ Manifolds ] [ Many-task ] [ mapping ] [ Markov chain Monte Carlo ] [ Markov Chain Monte Carlo ] [ Markov jump process ] [ Masked Reconstruction ] [ mathematical reasoning ] [ Matrix and Tensor Factorization ] [ matrix completion ] [ matrix decomposition ] [ Matrix Factorization ] [ max-margin ] [ MCMC ] [ MCMC sampling ] [ mean estimation ] [ mean-field dynamics ] [ mean separation ] [ Mechanism Design ] [ medical time series ] [ mel-filterbanks ] [ memorization ] [ Memorization ] [ Memory ] [ memory efficient ] [ memory efficient training ] [ Memory Mapping ] [ memory optimized training ] [ Memory-saving ] [ mesh ] [ Message Passing ] [ Message Passing GNNs ] [ meta-gradients ] [ Meta-learning ] [ Meta Learning ] [ Meta-Learning ] [ Metric Surrogate ] [ minimax optimal rate ] [ Minimax Optimization ] [ minimax risk ] [ Minmax ] [ min-max optimization ] [ mirror-prox ] [ Missing Data Inference ] [ Missing value imputation ] [ Missing Values ] [ misssing data ] [ mixed precision ] [ Mixed Precision ] [ Mixed-precision quantization ] [ mixture density nets ] [ mixture of experts ] [ mixup ] [ Mixup ] [ MixUp ] [ MLaaS ] [ MoCo ] [ Model Attribution ] [ model-based control ] [ model-based learning ] [ Model-based Reinforcement Learning ] [ Model-Based Reinforcement Learning ] [ model-based RL ] [ Model-based RL ] [ Model Biases ] [ Model compression ] [ model extraction ] [ model fairness ] [ Model Inversion ] [ model order reduction ] [ model ownership ] [ model predictive control ] [ model-predictive control ] [ Model Predictive Control ] [ Model privacy ] [ Models for code ] [ models of learning and generalization ] [ Model stealing ] [ Modern Hopfield Network ] [ modern Hopfield networks ] [ modified equation analysis ] [ modular architectures ] [ Modular network ] [ modular networks ] [ modular neural networks ] [ modular representations ] [ modulated convolution ] [ Molecular conformation generation ] [ molecular design ] [ Molecular Dynamics ] [ molecular graph generation ] [ Molecular Representation ] [ Molecule Design ] [ Momentum ] [ momentum methods ] [ momentum optimizer ] [ monotonicity ] [ Monte Carlo ] [ Monte-Carlo tree search ] [ Monte Carlo Tree Search ] [ morphology ] [ Morse theory ] [ mpc ] [ Multi-agent ] [ Multi-agent games ] [ Multiagent Learning ] [ multi-agent platform ] [ Multi-Agent Policy Gradients ] [ Multi-agent reinforcement learning ] [ Multi-agent Reinforcement Learning ] [ Multi-Agent Reinforcement Learning ] [ Multi-Agent Transfer Learning ] [ multiclass classification ] [ multi-dimensional discrete action spaces ] [ Multi-domain ] [ multi-domain disentanglement ] [ multi-head attention ] [ Multi-Hop ] [ multi-hop question answering ] [ Multi-hop Reasoning ] [ Multilingual Modeling ] [ multilingual representations ] [ multilingual transformer ] [ multilingual translation ] [ Multimodal ] [ Multi-Modal ] [ Multimodal Attention ] [ multi-modal learning ] [ Multimodal Learning ] [ Multi-Modal Learning ] [ Multimodal Spaces ] [ Multi-objective optimization ] [ multi-player ] [ Multiplicative Weights Update ] [ Multi-scale Representation ] [ multitask ] [ Multi-task ] [ Multi-task Learning ] [ Multi Task Learning ] [ Multi-Task Learning ] [ multi-task learning theory ] [ Multitask Reinforcement Learning ] [ Multi-view Learning ] [ Multi-View Learning ] [ Multi-view Representation Learning ] [ Mutual Information ] [ MuZero ] [ Named Entity Recognition ] [ NAS ] [ nash ] [ natural gradient descent ] [ Natural Language Processing ] [ natural scene statistics ] [ natural sparsity ] [ Negative Sampling ] [ negotiation ] [ nested optimization ] [ network architecture ] [ Network Architecture ] [ Network Inductive Bias ] [ network motif ] [ Network pruning ] [ Network Pruning ] [ networks ] [ network trainability ] [ network width ] [ Neural Architecture Search ] [ Neural Attention Distillation ] [ neural collapse ] [ Neural data compression ] [ Neural IR ] [ neural kernels ] [ neural link prediction ] [ Neural Model Explanation ] [ neural module network ] [ Neural Network ] [ Neural Network Bounding ] [ neural network calibration ] [ Neural Network Gaussian Process ] [ neural network robustness ] [ Neural networks ] [ Neural Networks ] [ neural network training ] [ Neural Network Verification ] [ neural ode ] [ Neural ODE ] [ Neural ODEs ] [ Neural operators ] [ Neural Physics Engines ] [ Neural Processes ] [ neural reconstruction ] [ neural sound synthesis ] [ neural spike train ] [ neural symbolic reasoning ] [ neural tangent kernel ] [ Neural tangent kernel ] [ Neural Tangent Kernel ] [ neural tangent kernels ] [ Neural text decoding ] [ neurobiology ] [ Neuroevolution ] [ Neuro symbolic ] [ Neuro-Symbolic Learning ] [ neuro-symbolic models ] [ NLI ] [ NLP ] [ Node Embeddings ] [ noise contrastive estimation ] [ Noise-contrastive learning ] [ Noise model ] [ noise robust learning ] [ Noisy Demonstrations ] [ noisy label ] [ Noisy Label ] [ Noisy Labels ] [ Non-asymptotic Confidence Intervals ] [ non-autoregressive generation ] [ nonconvex ] [ non-convex learning ] [ Non-Convex Optimization ] [ Non-IID ] [ nonlinear control theory ] [ nonlinear dynamical systems ] [ nonlinear Hawkes process ] [ nonlinear walk ] [ Non-Local Modules ] [ non-minimax optimization ] [ nonnegative PCA ] [ nonseparable Hailtonian system ] [ non-smooth models ] [ non-stationary stochastic processes ] [ no-regret learning ] [ normalized maximum likelihood ] [ normalize layer ] [ normalizers ] [ Normalizing Flow ] [ normalizing flows ] [ Normalizing flows ] [ Normalizing Flows ] [ normative models ] [ novelty-detection ] [ ntk ] [ number of linear regions ] [ numerical errors ] [ numerical linear algebra ] [ object-centric representations ] [ Object detection ] [ Object Detection ] [ object-keypoint representations ] [ ObjectNet ] [ Object Permanence ] [ Observational Imitation ] [ ODE ] [ offline ] [ offline/batch reinforcement learning ] [ off-line reinforcement learning ] [ offline reinforcement learning ] [ Offline Reinforcement Learning ] [ offline RL ] [ off-policy evaluation ] [ Off Policy Evaluation ] [ Off-policy policy evaluation ] [ Off-Policy Reinforcement Learning ] [ off-policy RL ] [ one-class-classification ] [ one-to-many mapping ] [ Open-domain ] [ open domain complex question answering ] [ open source ] [ Optimal Control Theory ] [ optimal convergence ] [ optimal power flow ] [ Optimal Transport ] [ optimal transport maps ] [ Optimisation for Deep Learning ] [ optimism ] [ Optimistic Gradient Descent Ascent ] [ Optimistic Mirror Decent ] [ Optimistic Multiplicative Weights Update ] [ Optimization ] [ order learning ] [ ordinary differential equation ] [ orthogonal ] [ orthogonal layers ] [ orthogonal machine learning ] [ Orthogonal Polynomials ] [ Oscillators ] [ outlier detection ] [ outlier-detection ] [ Outlier detection ] [ out-of-distribution ] [ Out-of-distribution detection in deep learning ] [ out-of-distribution generalization ] [ Out-of-domain ] [ over-fitting ] [ Overfitting ] [ overparameterisation ] [ over-parameterization ] [ Over-parameterization ] [ Overparameterization ] [ overparameterized neural networks ] [ Over-smoothing ] [ Oversmoothing ] [ over-squashing ] [ PAC Bayes ] [ padding ] [ parallel Monte Carlo Tree Search (MCTS) ] [ parallel tempering ] [ Parameter-Reduced MLR ] [ part-based ] [ Partial Amortization ] [ Partial differential equation ] [ partial differential equations ] [ partially observed environments ] [ particle inference ] [ pca ] [ pde ] [ pdes ] [ PDEs ] [ performer ] [ persistence diagrams ] [ personalized learning ] [ perturbation sets ] [ Peter-Weyl Theorem ] [ phase retrieval ] [ Physical parameter estimation ] [ physical reasoning ] [ physical scene understanding ] [ Physical Simulation ] [ physical symbol grounding ] [ physics ] [ physics-guided deep learning ] [ piecewise linear function ] [ pipeline toolkit ] [ plan-based reward shaping ] [ Planning ] [ Poincaré Ball Model ] [ Point cloud ] [ Point clouds ] [ point processes ] [ pointwise mutual information ] [ poisoning ] [ poisoning attack ] [ poisson matrix factorization ] [ policy learning ] [ Policy Optimization ] [ polynomial time ] [ Pose Estimation ] [ Position Embedding ] [ Position Encoding ] [ post-hoc calibration ] [ Post-Hoc Correction ] [ Post Training Quantization ] [ power grid management ] [ Predictive Modeling ] [ predictive uncertainty ] [ Predictive Uncertainty Estimation ] [ pretrained language model ] [ pretrained language model. ] [ pre-trained language model fine-tuning ] [ Pretrained Language Models ] [ Pretrained Text Encoders ] [ pre-training ] [ Pre-training ] [ Primitive Discovery ] [ principal components analysis ] [ Privacy ] [ privacy leakage from gradients ] [ privacy preserving machine learning ] [ Privacy-utility tradeoff ] [ probabelistic models ] [ probabilistic generative models ] [ probabilistic inference ] [ probabilistic matrix factorization ] [ Probabilistic Methods ] [ probabilistic multivariate forecasting ] [ probabilistic numerics ] [ probabilistic programs ] [ probably approximated correct guarantee ] [ Probe ] [ probing ] [ procedural generation ] [ procedural knowledge ] [ product of experts ] [ Product Quantization ] [ Program obfuscation ] [ Program Synthesis ] [ Proper Scoring Rules ] [ protein ] [ prototype propagation ] [ Provable Robustness ] [ provable sample efficiency ] [ proximal gradient descent-ascent ] [ proxy ] [ Pruning ] [ Pruning at initialization ] [ pseudo-labeling ] [ Pseudo-Labeling ] [ QA ] [ Q-learning ] [ Quantization ] [ quantum machine learning ] [ quantum mechanics ] [ Quantum Mechanics ] [ Question Answering ] [ random ] [ Random Feature ] [ Random Features ] [ Randomized Algorithms ] [ Random Matrix Theory ] [ Random Weights Neural Networks ] [ rank-collapse ] [ rank-constrained convex optimization ] [ rao ] [ rao-blackwell ] [ Rate-distortion optimization ] [ raven's progressive matrices ] [ real time recurrent learning ] [ real-world ] [ Real-world image denoising ] [ reasoning paths ] [ recommendation systems ] [ recommender system ] [ Recommender Systems ] [ recovery likelihood ] [ rectified linear unit ] [ Recurrent Generative Model ] [ Recurrent Neural Network ] [ Recurrent neural networks ] [ Recurrent Neural Networks ] [ recursive dense retrieval ] [ reformer ] [ regime agnostic methods ] [ Regression ] [ Regression without correspondence ] [ regret analysis ] [ regret minimization ] [ Regularization ] [ Regularization by denoising ] [ regularized markov decision processes ] [ Reinforcement ] [ Reinforcement learning ] [ Reinforcement Learning ] [ Reinforcement Learnings ] [ Reinforcement learning theory ] [ relabelling ] [ Relational regularized autoencoder ] [ Relation Extraction ] [ relaxed regularization ] [ relu network ] [ ReLU networks ] [ Rematerialization ] [ Render-and-Compare ] [ Reparameterization ] [ repetitions ] [ replica exchange ] [ representational learning ] [ representation analysis ] [ Representation learning ] [ Representation Learning ] [ representation learning for computer vision ] [ representation learning for robotics ] [ representation of dynamical systems ] [ Representation Theory ] [ reproducibility ] [ reproducible research ] [ Reproducing kernel Hilbert space ] [ resampling ] [ reset-free ] [ residual ] [ ResNets ] [ resource constrained ] [ Restricted Boltzmann Machines ] [ retraining ] [ Retrieval ] [ reverse accuracy ] [ reverse engineering ] [ reward learning ] [ reward randomization ] [ reward shaping ] [ reweighting ] [ Rich observation ] [ rich observations ] [ risk-averse ] [ Risk bound ] [ Risk Estimation ] [ risk sensitive ] [ rl ] [ RMSprop ] [ RNA-protein interaction prediction ] [ RNA structure ] [ RNA structure embedding ] [ RNN ] [ RNNs ] [ robotic manipulation ] [ robust ] [ robust control ] [ robust deep learning ] [ Robust Deep Learning ] [ robust learning ] [ Robust Learning ] [ Robust Machine Learning ] [ Robustness ] [ Robustness certificates ] [ Robust Overfitting ] [ ROC ] [ Role-Based Learning ] [ rooted graphs ] [ Rotation invariance ] [ rtrl ] [ Runtime Systems ] [ Saddle-point Optimization ] [ safe ] [ Safe exploration ] [ safe planning ] [ Saliency ] [ Saliency Guided Data Augmentation ] [ saliency maps ] [ SaliencyMix ] [ sample complexity separation ] [ Sample Efficiency ] [ sample information ] [ sample reweighting ] [ Sampling ] [ sampling algorithms ] [ Scalability ] [ Scale ] [ scale-invariant weights ] [ Scale of initialization ] [ scene decomposition ] [ scene generation ] [ Scene Understanding ] [ Science ] [ science of deep learning ] [ score-based generative models ] [ score matching ] [ score-matching ] [ SDE ] [ Second-order analysis ] [ second-order approximation ] [ second-order optimization ] [ Security ] [ segmented models ] [ selective classification ] [ Self-Imitation ] [ self supervised learning ] [ Self-supervised learning ] [ Self-supervised Learning ] [ Self Supervised Learning ] [ Self-Supervised Learning ] [ self-supervision ] [ self-training ] [ self-training theory ] [ semantic anomaly detection ] [ semantic directions in latent space ] [ semantic graphs ] [ Semantic Image Synthesis ] [ semantic parsing ] [ semantic role labeling ] [ semantic-segmentation ] [ Semantic Segmentation ] [ Semantic Textual Similarity ] [ semi-infinite duality ] [ semi-nonnegative matrix factorization ] [ semiparametric inference ] [ semi-supervised ] [ Semi-supervised Learning ] [ Semi-Supervised Learning ] [ semi-supervised learning theory ] [ Sentence Embeddings ] [ Sentence Representations ] [ Sentiment ] [ separation of variables ] [ Sequence Data ] [ Sequence Modeling ] [ sequence models ] [ Sequence-to-sequence learning ] [ sequence-to-sequence models ] [ sequential data ] [ Sequential probability ratio test ] [ Sequential Representation Learning ] [ set prediction ] [ set transformer ] [ SGD ] [ SGD noise ] [ sgld ] [ Shape ] [ shape bias ] [ Shape Bias ] [ Shape Encoding ] [ shapes ] [ Shapley values ] [ Sharpness Minimization ] [ side channel analysis ] [ Sigma Delta Quantization ] [ sign agnostic learning ] [ signal propagation ] [ signature ] [ sim2real ] [ sim2real transfer ] [ simple ] [ Singularity analysis ] [ singular value decomposition ] [ Sinkhorn algorithm ] [ skeleton-based action recognition ] [ sketch-based modeling ] [ sketches ] [ Skill Discovery ] [ SLAM ] [ sliced fused Gromov Wasserstein ] [ Sliced Wasserstein ] [ Slowdown attacks ] [ slowness ] [ Smooth games ] [ smoothing ] [ SMT Solvers ] [ social perception ] [ Soft Body ] [ soft labels ] [ software ] [ sound classification ] [ sound spatialization ] [ Source Code ] [ sparse Bayesian learning ] [ Sparse Embedding ] [ sparse embeddings ] [ sparse reconstruction ] [ sparse representation ] [ sparse representations ] [ sparse stochastic gates ] [ Sparsity ] [ Sparsity Learning ] [ spatial awareness ] [ spatial bias ] [ spatial uncertainty ] [ spatio-temporal forecasting ] [ spatio-temporal graph ] [ spatio-temporal modeling ] [ spatio-temporal modelling ] [ spatiotemporal prediction ] [ Spatiotemporal Understanding ] [ Spectral Analysis ] [ Spectral Distribution ] [ Spectral Graph Filter ] [ spectral regularization ] [ speech generation ] [ speech-impaired ] [ speech processing ] [ speech recognition. ] [ Speech Recognition ] [ spherical distributions ] [ spiking neural network ] [ spurious correlations ] [ square loss vs cross-entropy ] [ stability theory ] [ State abstraction ] [ state abstractions ] [ state-space models ] [ statistical learning theory ] [ Statistical Learning Theory ] [ statistical physics ] [ Statistical Physics ] [ statistical physics methods ] [ Steerable Kernel ] [ Stepsize optimization ] [ stochastic asymptotics ] [ stochastic control ] [ (stochastic) gradient descent ] [ Stochastic Gradient Descent ] [ stochastic gradient Langevin dynamics ] [ stochastic process ] [ Stochastic Processes ] [ stochastic subgradient method ] [ Storage Capacity ] [ straight-through ] [ straightthrough ] [ strategic behavior ] [ Streaming ASR ] [ structural biology ] [ structural credit assignment ] [ structural inductive bias ] [ Structured Pruning ] [ Structure learning ] [ structure prediction ] [ structures prediction ] [ Style Mixing ] [ Style Transfer ] [ subgraph reasoning. ] [ sublinear ] [ submodular optimization ] [ Subspace clustering ] [ Summarization ] [ summary statistics ] [ superpixel ] [ supervised contrastive learning ] [ Supervised Deep Networks ] [ Supervised Learning ] [ support estimation ] [ surprisal ] [ surrogate models ] [ svd ] [ SVD ] [ Symbolic Methods ] [ symbolic regression ] [ symbolic representations ] [ Symmetry ] [ symplectic networks ] [ Syntax ] [ Synthetic benchmark dataset ] [ synthetic-to-real generalization ] [ Systematic generalisation ] [ Systematicity ] [ System identification ] [ Tabular ] [ tabular data ] [ Tabular Data ] [ targeted attack ] [ Task Embeddings ] [ task generation ] [ task-oriented dialogue ] [ Task-oriented Dialogue System ] [ task reduction ] [ Task Segmentation ] [ Teacher-Student Learning ] [ teacher-student model ] [ temporal context ] [ Temporal knowledge graph ] [ temporal networks ] [ tensor product ] [ Text-based Games ] [ Text Representation ] [ Text Retrieval ] [ Text to speech ] [ Text to speech synthesis ] [ text-to-sql ] [ Texture ] [ Texture Bias ] [ Textworld ] [ Theorem proving ] [ theoretical issues in deep learning ] [ theoretical limits ] [ theoretical study ] [ Theory ] [ Theory of deep learning ] [ theory of mind ] [ Third-Person Imitation ] [ Thompson sampling ] [ time-frequency representations ] [ timescale ] [ timescales ] [ Time Series ] [ Time series forecasting ] [ time series prediction ] [ topic modelling ] [ Topology ] [ training dynamics ] [ Training Method ] [ trajectory ] [ trajectory optimization ] [ trajectory prediction ] [ Transferability ] [ Transfer learning ] [ Transfer Learning ] [ transformation invariance ] [ Transformer ] [ Transformers ] [ traveling salesperson problem ] [ Tree-structured Data ] [ trembl ] [ tropical function ] [ trust region ] [ two-layer neural network ] [ Uncertainty ] [ uncertainty calibration ] [ Uncertainty estimates ] [ Uncertainty estimation ] [ Uncertainty Machine Learning ] [ understanding ] [ understanding CNNs ] [ Understanding Data Augmentation ] [ understanding decision-making ] [ understanding deep learning ] [ Understanding Deep Learning ] [ understanding neural networks ] [ U-Net ] [ unidirectional ] [ uniprot ] [ universal approximation ] [ Universal approximation ] [ Universality ] [ universal representation learning ] [ universal sound separation ] [ unlabeled data ] [ Unlabeled Entity Problem ] [ Unlearnable Examples ] [ unrolled algorithms ] [ Unsupervised denoising ] [ Unsupervised Domain Translation ] [ unsupervised image denoising ] [ Unsupervised learning ] [ Unsupervised Learning ] [ unsupervised learning theory ] [ unsupervised loss ] [ Unsupervised Meta-learning ] [ unsupervised object discovery ] [ Unsupervised reinforcement learning ] [ unsupervised skill discovery ] [ unsupervised stabilization ] [ Upper Confidence bound applied to Trees (UCT) ] [ Usable Information ] [ VAE ] [ Value factorization ] [ value learning ] [ vanishing gradient problem ] [ variable binding ] [ variable convergence ] [ Variable Embeddings ] [ Variance Networks ] [ Variational Auto-encoder ] [ Variational autoencoders ] [ Variational Autoencoders ] [ Variational inference ] [ variational information bottleneck ] [ Verification ] [ video analysis ] [ Video Classification ] [ Video Compression ] [ video generation ] [ video-grounded dialogues ] [ Video prediction ] [ Video Reasoning ] [ video recognition ] [ Video Recognition ] [ video representation learning ] [ video synthesis ] [ video-text learning ] [ views ] [ virtual environment ] [ vision-and-language-navigation ] [ visual counting ] [ visualization ] [ visual perception ] [ Visual Reasoning ] [ visual reinforcement learning ] [ visual representation learning ] [ visual saliency ] [ vocoder ] [ voice conversion ] [ Volume Analysis ] [ VQA ] [ vulnerability of RL ] [ wanet ] [ warping functions ] [ Wasserstein ] [ wasserstein-2 barycenters ] [ wasserstein-2 distance ] [ Wasserstein distance ] [ waveform generation ] [ weakly-supervised learning ] [ weakly supervised representation learning ] [ Weak supervision ] [ Weak-supervision ] [ webly-supervised learning ] [ weight attack ] [ weight balance ] [ Weight quantization ] [ weight-sharing ] [ wide local minima ] [ Wigner-Eckart Theorem ] [ winning tickets ] [ wireframe model ] [ word-learning ] [ world models ] [ World Models ] [ worst-case generalisation ] [ xai ] [ XAI ] [ zero-order optimization ] [ zero-shot learning ] [ Zero-shot learning ] [ Zero-shot Learning ] [ Zero-shot synthesis ]

915 Results

Poster
Mon 1:00 Does enhanced shape bias improve neural network robustness to common corruptions?
Chaithanya Kumar Mummadi, Ranjitha Subramaniam, Robin Hutmacher, Julien Vitay, Volker Fischer, Jan Hendrik Metzen
Poster
Mon 1:00 Implicit Normalizing Flows
Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu
Poster
Mon 1:00 Revisiting Locally Supervised Learning: an Alternative to End-to-end Training
Yulin Wang, Zanlin Ni, Shiji Song, Le Yang, Gao Huang
Poster
Mon 1:00 Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
Pim De Haan, Maurice Weiler, Taco Cohen, Max Welling
Poster
Mon 1:00 SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization
A F M Shahab Uddin, Mst. Sirazam Monira, Wheemyung Shin, TaeChoong Chung, Sung-Ho Bae
Poster
Mon 1:00 Solving Compositional Reinforcement Learning Problems via Task Reduction
Yunfei Li, Yilin Wu, Huazhe Xu, Xiaolong Wang, Yi Wu
Poster
Mon 1:00 MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
Tsz Him Cheung, Dit-Yan Yeung
Poster
Mon 1:00 FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders
Pengyu Cheng, Weituo Hao, Siyang Yuan, Shijing Si, Lawrence Carin
Poster
Mon 1:00 Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering
Calypso Herrera, Florian Krach, Josef Teichmann
Poster
Mon 1:00 Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets
Hayeon Lee, Eunyoung Hyung, Sung Ju Hwang
Poster
Mon 1:00 LEAF: A Learnable Frontend for Audio Classification
Neil Zeghidour, Olivier Teboul, Félix de Chaumont Quitry, Marco Tagliasacchi
Poster
Mon 1:00 Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data
Francesco Tonolini, Pablo Garcia Moreno, Andreas Damianou, Roderick Murray-Smith
Poster
Mon 1:00 Spatially Structured Recurrent Modules
Nasim Rahaman, Anirudh Goyal, Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schoelkopf
Poster
Mon 1:00 Towards Robustness Against Natural Language Word Substitutions
Xinshuai Dong, Anh Tuan Luu, Rongrong Ji, Hong Liu
Poster
Mon 1:00 Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU
Patrick Kidger, Terry Lyons
Poster
Mon 1:00 Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Cheng Wang, Carolin Lawrence, Mathias Niepert
Poster
Mon 1:00 Progressive Skeletonization: Trimming more fat from a network at initialization
Pau de Jorge Aranda, Amartya Sanyal, Harkirat Singh Behl, Philip Torr, Grégory Rogez, Puneet Dokania
Poster
Mon 1:00 On Learning Universal Representations Across Languages
Xiangpeng Wei, Rongxiang Weng, Yue Hu, Luxi Xing, Heng Yu, Weihua Luo
Poster
Mon 1:00 Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability
Suraj Srinivas, François Fleuret
Poster
Mon 1:00 A Unified Approach to Interpreting and Boosting Adversarial Transferability
Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
Poster
Mon 1:00 QPLEX: Duplex Dueling Multi-Agent Q-Learning
Jianhao Wang, Zhizhou Ren, Terry Liu, Yang Yu, Chongjie Zhang
Poster
Mon 1:00 Overfitting for Fun and Profit: Instance-Adaptive Data Compression
Ties van Rozendaal, Iris Huijben, Taco Cohen
Poster
Mon 1:00 PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences
Hehe Fan, Xin Yu, Yuhang Ding, Yi Yang, Mohan Kankanhalli
Poster
Mon 1:00 Set Prediction without Imposing Structure as Conditional Density Estimation
David W Zhang, Gertjan J Burghouts, Cees G Snoek
Poster
Mon 1:00 Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient Detectors
Linfeng Zhang, Kaisheng Ma
Poster
Mon 1:00 Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet
Poster
Mon 1:00 Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits
Jiawang Bai, Baoyuan Wu, Yong Zhang, Yiming Li, Zhifeng Li, Shu-Tao Xia
Poster
Mon 1:00 Noise against noise: stochastic label noise helps combat inherent label noise
Pengfei Chen, Guangyong Chen, Junjie Ye, jingwei zhao, Pheng-Ann Heng
Poster
Mon 1:00 Predicting Infectiousness for Proactive Contact Tracing
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B Muller, Meng Qu, victor schmidt, Pierre-luc St-charles, hannah alsdurf, Olexa Bilaniuk, david buckeridge, Gaétan Marceau Caron, pierre carrier, Joumana Ghosn, satya gagne, Chris J Pal, Irina Rish, Bernhard Schoelkopf, abhinav sharma, Jian Tang, Andrew Williams
Poster
Mon 1:00 Trusted Multi-View Classification
Zongbo Han, Changqing Zhang, Huazhu FU, Joey T Zhou
Poster
Mon 1:00 The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods
Louis THIRY, Michael Arbel, Eugene Belilovsky, Edouard Oyallon
Poster
Mon 1:00 Semantic Re-tuning with Contrastive Tension
Fredrik Carlsson, Amaru C Gyllensten, Evangelia Gogoulou, Erik Y Hellqvist, Magnus Sahlgren
Poster
Mon 1:00 Temporally-Extended ε-Greedy Exploration
Will Dabney, Georg Ostrovski, Andre Barreto
Poster
Mon 1:00 Exploring Balanced Feature Spaces for Representation Learning
Bingyi Kang, Yu Li, Sain Xie, Zehuan Yuan, Jiashi Feng
Poster
Mon 1:00 Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch
Aojun Zhou, Yukun Ma, Junnan Zhu, Jianbo Liu, Zhijie Zhang, Kun Yuan, Wenxiu Sun, Hongsheng Li
Poster
Mon 1:00 What Makes Instance Discrimination Good for Transfer Learning?
Nanxuan Zhao, Zhirong Wu, Rynson W Lau, Stephen Lin
Poster
Mon 1:00 Isometric Transformation Invariant and Equivariant Graph Convolutional Networks
Masanobu Horie, Naoki Morita, Toshiaki Hishinuma, Yu Ihara, Naoto Mitsume
Poster
Mon 1:00 Domain Generalization with MixStyle
Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
Poster
Mon 1:00 MELR: Meta-Learning via Modeling Episode-Level Relationships for Few-Shot Learning
Nanyi Fei, Zhiwu Lu, Tao Xiang, Songfang Huang
Poster
Mon 1:00 Wasserstein Embedding for Graph Learning
Soheil Kolouri, Navid Naderializadeh, Gustavo K Rohde, Heiko Hoffmann
Poster
Mon 1:00 ResNet After All: Neural ODEs and Their Numerical Solution
Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann
Poster
Mon 1:00 Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron Courville, Zhanxing Zhu
Poster
Mon 1:00 MetaNorm: Learning to Normalize Few-Shot Batches Across Domains
Yingjun Du, Xiantong Zhen, Ling Shao, Cees G Snoek
Poster
Mon 1:00 A Good Image Generator Is What You Need for High-Resolution Video Synthesis
Yu Tian, Jian Ren, Menglei Chai, Kyle Olszewski, Xi Peng, Dimitris Metaxas, Sergey Tulyakov
Poster
Mon 1:00 Scalable Transfer Learning with Expert Models
Joan Puigcerver Puigcerver i Perez, Carlos Riquelme, Basil Mustafa, Cedric Renggli, André Susano Pinto, Sylvain Gelly, Daniel Keysers, Neil Houlsby
Poster
Mon 1:00 WaNet - Imperceptible Warping-based Backdoor Attack
Tuan Anh Nguyen, Anh T Tran
Poster
Mon 1:00 Training with Quantization Noise for Extreme Model Compression
Pierre Stock, Angela Fan, Benjamin Graham, Edouard Grave, Rémi Gribonval, Hervé Jégou, Armand Joulin
Poster
Mon 1:00 On the Transfer of Disentangled Representations in Realistic Settings
Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schoelkopf
Poster
Mon 1:00 Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning
Dong Bok Lee, Dongchan Min, Seanie Lee, Sung Ju Hwang
Poster
Mon 1:00 Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
Xinyue Chen, Che Wang, Zijian Zhou, Keith Ross
Oral
Mon 3:00 Dataset Condensation with Gradient Matching
Bo ZHAO, Konda Reddy Mopuri, Hakan Bilen
Oral
Mon 3:15 Free Lunch for Few-shot Learning: Distribution Calibration
Shuo Yang, Lu Liu, Min Xu
Spotlight
Mon 3:30 Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet
Spotlight
Mon 3:40 Generalization in data-driven models of primary visual cortex
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Jagadish, Eric Wang, Edgar Walker, Santiago Cadena Cadena, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
Oral
Mon 4:15 A Distributional Approach to Controlled Text Generation
Muhammad Khalifa, Hady Elsahar, Marc Dymetman
Spotlight
Mon 4:30 The Intrinsic Dimension of Images and Its Impact on Learning
Phil Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
Spotlight
Mon 4:40 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Oral
Mon 5:00 Geometry-aware Instance-reweighted Adversarial Training
Jingfeng Zhang, Jianing ZHU, Gang Niu, Bo Han, Masashi Sugiyama, Mohan Kankanhalli
Oral
Mon 5:15 Do 2D GANs Know 3D Shape? Unsupervised 3D Shape Reconstruction from 2D Image GANs
Xingang Pan, Bo DAI, Ziwei Liu, Chen Change Loy, Ping Luo
Oral
Mon 5:30 Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability
Suraj Srinivas, François Fleuret
Spotlight
Mon 5:45 Contrastive Divergence Learning is a Time Reversal Adversarial Game
Omer Yair, Tomer Michaeli
Mon 6:00 WiML@ICLR 2021 Virtual Panel
Invited Talk
Mon 8:00 Moving beyond the fairness rhetoric in machine learning
Timnit Gebru
Poster
Mon 9:00 Learning Structural Edits via Incremental Tree Transformations
Ziyu Yao, Frank F Xu, Pengcheng Yin, Huan Sun, Graham Neubig
Poster
Mon 9:00 Training GANs with Stronger Augmentations via Contrastive Discriminator
Jongheon Jeong, Jinwoo Shin
Poster
Mon 9:00 Language-Agnostic Representation Learning of Source Code from Structure and Context
Daniel Zügner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Günnemann
Poster
Mon 9:00 Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs
Matthew Leavitt, Ari Morcos
Poster
Mon 9:00 Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
Garrett Honke, Irina Higgins, Nina Thigpen, Vladimir Miskovic, Katie Link, Sunny Duan, Pramod Gupta, Julia Klawohn, Greg Hajcak
Poster
Mon 9:00 Multi-Level Local SGD: Distributed SGD for Heterogeneous Hierarchical Networks
Timothy Castiglia, Anirban Das, Stacy Patterson
Poster
Mon 9:00 Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation
Biao Zhang, Ankur Bapna, Rico Sennrich, Orhan Firat
Poster
Mon 9:00 What Should Not Be Contrastive in Contrastive Learning
Tete Xiao, Xiaolong Wang, Alyosha Efros, trevor darrell
Poster
Mon 9:00 Trajectory Prediction using Equivariant Continuous Convolution
Robin Walters, Jinxi Li, Rose Yu
Poster
Mon 9:00 Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
Denis Yarats, Ilya Kostrikov, Rob Fergus
Poster
Mon 9:00 Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
Ben Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov
Poster
Mon 9:00 On the role of planning in model-based deep reinforcement learning
Jessica Hamrick, Abram Friesen, Feryal Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Buesing, Petar Veličković, Theo Weber
Poster
Mon 9:00 Fast convergence of stochastic subgradient method under interpolation
Huang Fang, Zhenan Fan, Michael Friedlander
Poster
Mon 9:00 MoVie: Revisiting Modulated Convolutions for Visual Counting and Beyond
Duy-Kien Nguyen, Vedanuj Goswami, Xinlei Chen
Poster
Mon 9:00 Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning
Zhenfang Chen, Jiayuan Mao, Jiajun Wu, Kwan-Yee K Wong, Joshua B Tenenbaum, Chuang Gan
Poster
Mon 9:00 NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation
Angtian Wang, Adam Kortylewski, Alan Yuille
Poster
Mon 9:00 Learning from others' mistakes: Avoiding dataset biases without modeling them
Victor Sanh, Thomas Wolf, Yonatan Belinkov, Alexander M Rush
Poster
Mon 9:00 On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Marius Mosbach, Maksym Andriushchenko, Dietrich Klakow
Poster
Mon 9:00 Scaling Symbolic Methods using Gradients for Neural Model Explanation
Subham Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick Riley
Poster
Mon 9:00 What Can You Learn From Your Muscles? Learning Visual Representation from Human Interactions
Kiana Ehsani, Daniel Gordon, Thomas H Nguyen, Roozbeh Mottaghi, Ali Farhadi
Poster
Mon 9:00 On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
Poster
Mon 9:00 Predicting Inductive Biases of Pre-Trained Models
Charles Lovering, Rohan Jha, Tal Linzen, Ellie Pavlick
Poster
Mon 9:00 MultiModalQA: complex question answering over text, tables and images
Alon Talmor, Ori Yoran, Amnon Catav, Dan Lahav, Yizhong Wang, Akari Asai, Gabriel Ilharco, Hannaneh Hajishirzi, Jonathan Berant
Poster
Mon 9:00 Open Question Answering over Tables and Text
wenhu chen, Ming-Wei Chang, Eva Schlinger, William Yang Wang, William Cohen
Poster
Mon 9:00 Parameter Efficient Multimodal Transformers for Video Representation Learning
Sangho Lee, Youngjae Yu, Gunhee Kim, Thomas Breuel, Jan Kautz, Yale Song
Poster
Mon 9:00 InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective
Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu
Poster
Mon 9:00 Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
Csaba Toth, Patric Bonnier, Harald Oberhauser
Poster
Mon 9:00 A statistical theory of cold posteriors in deep neural networks
Laurence Aitchison
Poster
Mon 9:00 Understanding the failure modes of out-of-distribution generalization
Vaishnavh Nagarajan, Anders J Andreassen, Behnam Neyshabur
Poster
Mon 9:00 Single-Photon Image Classification
Thomas Fischbacher, Luciano Sbaiz
Poster
Mon 9:00 Reset-Free Lifelong Learning with Skill-Space Planning
Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch
Poster
Mon 9:00 Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures
Pedro Hermosilla Casajus, Marco Schäfer, Matej Lang, Gloria Fackelmann, Pere-Pau Vázquez, Barbora Kozlikova, Michael Krone, Tobias Ritschel, Timo Ropinski
Poster
Mon 9:00 Overparameterisation and worst-case generalisation: friend or foe?
Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar
Poster
Mon 9:00 GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing
Tao Yu, Jason Wu, Xi V Lin, bailin wang, Yi Tan, Xinyi Yang, Dragomir Radev, Richard Socher, Caiming Xiong
Poster
Mon 9:00 LambdaNetworks: Modeling long-range Interactions without Attention
Irwan Bello
Poster
Mon 9:00 Adaptive Federated Optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, Brendan McMahan
Poster
Mon 9:00 Using latent space regression to analyze and leverage compositionality in GANs
Lucy Chai, Jonas Wulff, Phillip Isola
Poster
Mon 9:00 Shape-Texture Debiased Neural Network Training
Yinigwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan Yuille, Cihang Xie
Poster
Mon 9:00 Multi-Time Attention Networks for Irregularly Sampled Time Series
Satya Narayan Shukla, Benjamin M Marlin
Poster
Mon 9:00 Saliency is a Possible Red Herring When Diagnosing Poor Generalization
Joseph Viviano, Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen
Poster
Mon 9:00 Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang, Rowan T McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
Poster
Mon 9:00 Zero-Cost Proxies for Lightweight NAS
Mohamed Abdelfattah, Abhinav Mehrotra, Łukasz Dudziak, Nic Lane
Poster
Mon 9:00 Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds
Efthymios Tzinis, Scott Wisdom, Aren Jansen, Shawn Hershey, Tal Remez, Dan Ellis, John Hershey
Poster
Mon 9:00 Sparse encoding for more-interpretable feature-selecting representations in probabilistic matrix factorization
Joshua Chang, Patrick A Fletcher, Jungmin Han, Ted Chang, Shashaank Vattikuti, Bart Desmet, Ayah Zirikly, Carson Chow
Poster
Mon 9:00 On the Universality of Rotation Equivariant Point Cloud Networks
Nadav Dym, Haggai Maron
Poster
Mon 9:00 Planning from Pixels using Inverse Dynamics Models
Keiran Paster, Sheila McIlraith, Jimmy Ba
Poster
Mon 9:00 Shapley explainability on the data manifold
Christopher Frye, Damien De Mijolla, Tom Begley, Laurence Cowton, Megan Stanley, Ilya Feige
Poster
Mon 9:00 Rethinking Embedding Coupling in Pre-trained Language Models
Hyung Won Chung, Thibault Fevry, Henry Tsai, Melvin Johnson, Sebastian Ruder
Poster
Mon 9:00 Learning "What-if" Explanations for Sequential Decision-Making
Ioana Bica, Dan Jarrett, Alihan Hüyük, Mihaela van der Schaar
Poster
Mon 9:00 Graph Convolution with Low-rank Learnable Local Filters
Xiuyuan Cheng, Zichen Miao, Qiang Qiu
Poster
Mon 9:00 Uncertainty Sets for Image Classifiers using Conformal Prediction
Anastasios Angelopoulos, Stephen Bates, Michael Jordan, Jitendra Malik
Poster
Mon 9:00 Conditional Negative Sampling for Contrastive Learning of Visual Representations
Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah Goodman
Poster
Mon 9:00 The Risks of Invariant Risk Minimization
Elan Rosenfeld, Pradeep K Ravikumar, Andrej Risteski
Poster
Mon 9:00 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Poster
Mon 9:00 Shapley Explanation Networks
Rui Wang, Xiaoqian Wang, David Inouye
Poster
Mon 9:00 X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback
Jensen Gao, Siddharth Reddy, Glen Berseth, Nick Hardy, Nikhilesh Natraj, Karunesh Ganguly, Anca Dragan, Sergey Levine
Poster
Mon 9:00 The role of Disentanglement in Generalisation
Milton Montero, Casimir JH Ludwig, Rui Ponte Costa, Gaurav Malhotra, Jeffrey Bowers
Poster
Mon 9:00 Structured Prediction as Translation between Augmented Natural Languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, RISHITA ANUBHAI, Cicero Nogueira dos Santos, Bing Xiang, Stefano Soatto
Poster
Mon 9:00 Rapid Task-Solving in Novel Environments
Samuel Ritter, Ryan Faulkner, Laurent Sartran, Adam Santoro, Matthew Botvinick, David Raposo
Poster
Mon 9:00 Extracting Strong Policies for Robotics Tasks from Zero-Order Trajectory Optimizers
Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes, Georg Martius
Poster
Mon 9:00 Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models
Siavash Khodadadeh, Sharare Zehtabian, Saeed Vahidian, Weijia Wang, Bill Lin, Ladislau Boloni
Oral
Mon 11:00 Federated Learning Based on Dynamic Regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas, Matthew Mattina, Paul Whatmough, Venkatesh Saligrama
Oral
Mon 11:30 Growing Efficient Deep Networks by Structured Continuous Sparsification
Xin Yuan, Pedro Savarese, Michael Maire
Spotlight
Mon 12:05 Generalization bounds via distillation
Daniel Hsu, Ziwei Ji, Matus Telgarsky, Lan Wang
Spotlight
Mon 12:15 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Spotlight
Mon 12:25 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
Spotlight
Mon 12:35 Systematic generalisation with group invariant predictions
Faruk Ahmed, Yoshua Bengio, Harm van Seijen, Aaron Courville
Spotlight
Mon 12:45 On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
Spotlight
Mon 12:55 Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images
Rewon Child
Spotlight
Mon 13:20 Uncertainty Sets for Image Classifiers using Conformal Prediction
Anastasios Angelopoulos, Stephen Bates, Michael Jordan, Jitendra Malik
Spotlight
Mon 13:30 PMI-Masking: Principled masking of correlated spans
Yoav Levine, Barak Lenz, Opher Lieber, Omri Abend, Kevin Leyton-Brown, Moshe Tennenholtz, Yoav Shoham
Spotlight
Mon 13:40 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao
Spotlight
Mon 14:00 Predicting Infectiousness for Proactive Contact Tracing
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B Muller, Meng Qu, victor schmidt, Pierre-luc St-charles, hannah alsdurf, Olexa Bilaniuk, david buckeridge, Gaétan Marceau Caron, pierre carrier, Joumana Ghosn, satya gagne, Chris J Pal, Irina Rish, Bernhard Schoelkopf, abhinav sharma, Jian Tang, Andrew Williams
Poster
Mon 17:00 Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
Karan Goel, Albert Gu, Yixuan Li, Christopher Re
Poster
Mon 17:00 Selective Classification Can Magnify Disparities Across Groups
Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang
Poster
Mon 17:00 Variational Intrinsic Control Revisited
Taehwan Kwon
Poster
Mon 17:00 Rethinking Architecture Selection in Differentiable NAS
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
Poster
Mon 17:00 Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation
Justin Fu, Sergey Levine
Poster
Mon 17:00 Partitioned Learned Bloom Filters
Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska
Poster
Mon 17:00 Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks
Alexander Levine, Soheil Feizi
Poster
Mon 17:00 On the geometry of generalization and memorization in deep neural networks
Cory Stephenson, Suchi Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung
Poster
Mon 17:00 Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks
Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Daniel Ma
Poster
Mon 17:00 Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
Rui Wang, Robin Walters, Rose Yu
Poster
Mon 17:00 SAFENet: A Secure, Accurate and Fast Neural Network Inference
Qian Lou, Yilin Shen, Hongxia Jin, Lei Jiang
Poster
Mon 17:00 MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training
Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan L Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Re
Poster
Mon 17:00 Learning A Minimax Optimizer: A Pilot Study
Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang
Poster
Mon 17:00 When Optimizing $f$-Divergence is Robust with Label Noise
Jiaheng Wei, Yang Liu
Poster
Mon 17:00 The Intrinsic Dimension of Images and Its Impact on Learning
Phil Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
Poster
Mon 17:00 SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing
Tao Yu, Rui Zhang, Alex Polozov, Christopher Meek, Ahmed H Awadallah
Poster
Mon 17:00 Optimal Regularization can Mitigate Double Descent
Preetum Nakkiran, Prayaag Venkat, Sham M Kakade, Tengyu Ma
Poster
Mon 17:00 Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification
Yingxue Zhou, Steven Wu, Arindam Banerjee
Poster
Mon 17:00 Taking Notes on the Fly Helps Language Pre-Training
Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
Poster
Mon 17:00 Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting
Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E Gonzalez, Marcus Rohrbach, trevor darrell
Poster
Mon 17:00 Rethinking Positional Encoding in Language Pre-training
Guolin Ke, Di He, Tie-Yan Liu
Poster
Mon 17:00 Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods
Taiji Suzuki, Akiyama Shunta
Poster
Mon 17:00 Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients
Jing An, Lexing Ying, Yuhua Zhu
Poster
Mon 17:00 Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang, Daniel Ma, Sarah Erfani, James Bailey, Yisen Wang
Poster
Mon 17:00 WaveGrad: Estimating Gradients for Waveform Generation
Nanxin Chen, Yu Zhang, Heiga Zen, Ron Weiss, Mohammad Norouzi, William Chan
Poster
Mon 17:00 One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
Poster
Mon 17:00 Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images
Rewon Child
Poster
Mon 17:00 UPDeT: Universal Multi-agent RL via Policy Decoupling with Transformers
Siyi Hu, Fengda Zhu, Xiaojun Chang, Xiaodan Liang
Poster
Mon 17:00 What are the Statistical Limits of Offline RL with Linear Function Approximation?
Ruosong Wang, Dean Foster, Sham M Kakade
Poster
Mon 17:00 DeLighT: Deep and Light-weight Transformer
Sachin Mehta, Marjan Ghazvininejad, Srini Iyer, Luke Zettlemoyer, Hannaneh Hajishirzi
Poster
Mon 17:00 On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning
Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Lily Weng, Chuang Gan, Meng Wang
Poster
Mon 17:00 MALI: A memory efficient and reverse accurate integrator for Neural ODEs
Juntang Zhuang, Nicha C Dvornek, sekhar tatikonda, James s Duncan
Poster
Mon 17:00 Robust Reinforcement Learning on State Observations with Learned Optimal Adversary
Huan Zhang, Hongge Chen, Duane S Boning, Cho-Jui Hsieh
Poster
Mon 17:00 Explaining the Efficacy of Counterfactually Augmented Data
Divyansh Kaushik, Amrith Setlur, Eduard H Hovy, Zachary Lipton
Poster
Mon 17:00 Layer-adaptive Sparsity for the Magnitude-based Pruning
Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin
Poster
Mon 17:00 PseudoSeg: Designing Pseudo Labels for Semantic Segmentation
Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister
Poster
Mon 17:00 When does preconditioning help or hurt generalization?
Shun-ichi Amari, Jimmy Ba, Roger Grosse, Chen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu
Poster
Mon 17:00 Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning
Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang
Poster
Mon 17:00 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang, trevor darrell
Poster
Mon 17:00 Latent Skill Planning for Exploration and Transfer
Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti
Poster
Mon 17:00 Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy
Akinori Ebihara, Taiki Miyagawa, Kazuyuki Sakurai, Hitoshi Imaoka
Poster
Mon 17:00 SOLAR: Sparse Orthogonal Learned and Random Embeddings
Tharun Medini Medini, Beidi Chen, Anshumali Shrivastava
Poster
Mon 17:00 Decentralized Attribution of Generative Models
Changhoon Kim, Yi Ren, 'YZ' Yezhou Yang
Poster
Mon 17:00 MixKD: Towards Efficient Distillation of Large-scale Language Models
Kevin Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin
Poster
Mon 17:00 Robust Curriculum Learning: from clean label detection to noisy label self-correction
Tianyi Zhou, Shengjie Wang, Jeff Bilmes
Poster
Mon 17:00 Learning a Latent Simplex in Input Sparsity Time
Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David Woodruff, Samson Zhou
Poster
Mon 17:00 Tilted Empirical Risk Minimization
Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith
Poster
Mon 17:00 VA-RED$^2$: Video Adaptive Redundancy Reduction
Bowen Pan, Rameswar Panda, Camilo L Fosco, Chung-Ching Lin, Alex J Andonian, Yue Meng, Kate Saenko, Aude Oliva, Rogerio Feris
Poster
Mon 17:00 Random Feature Attention
Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah Smith, Lingpeng Kong
Poster
Mon 17:00 Personalized Federated Learning with First Order Model Optimization
Michael Zhang, Karan Sapra, Sanja Fidler, Serena Yeung, Jose M. Alvarez
Poster
Mon 17:00 Zero-shot Synthesis with Group-Supervised Learning
Yunhao Ge, Sami Abu-El-Haija, Gan Xin, Laurent Itti
Poster
Mon 17:00 Learning Energy-Based Models by Diffusion Recovery Likelihood
Ruiqi Gao, Yang Song, Ben Poole, Yingnian Wu, Durk Kingma
Poster
Mon 17:00 Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Durk Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
Poster
Mon 17:00 Undistillable: Making A Nasty Teacher That CANNOT teach students
Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang
Poster
Mon 17:00 Meta-Learning with Neural Tangent Kernels
Yufan Zhou, Zhenyi Wang, Jiayi Xian, Changyou Chen, Jinhui Xu
Poster
Mon 17:00 Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
Junwen Bai, Weiran Wang, Yingbo Zhou, Caiming Xiong
Poster
Mon 17:00 MoPro: Webly Supervised Learning with Momentum Prototypes
Junnan Li, Caiming Xiong, Steven Hoi
Poster
Mon 17:00 Federated Learning Based on Dynamic Regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas, Matthew Mattina, Paul Whatmough, Venkatesh Saligrama
Poster
Mon 17:00 Contextual Transformation Networks for Online Continual Learning
Quang Pham, Chenghao Liu, Doyen Sahoo, Steven HOI
Poster
Mon 17:00 Deberta: Decoding-Enhanced Bert With Disentangled Attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen
Poster
Mon 17:00 SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
Mikhail Yurochkin, Yuekai Sun
Oral
Mon 19:00 SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments
Glen Berseth, Daniel Geng, Coline M Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
Oral
Mon 19:15 Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kin-Ho Lam, Alan Fern
Spotlight
Mon 19:45 Structured Prediction as Translation between Augmented Natural Languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, RISHITA ANUBHAI, Cicero Nogueira dos Santos, Bing Xiang, Stefano Soatto
Spotlight
Mon 19:55 Mathematical Reasoning via Self-supervised Skip-tree Training
Markus Rabe, Dennis Lee, Kshitij Bansal, Christian Szegedy
Spotlight
Mon 20:18 Improving Adversarial Robustness via Channel-wise Activation Suppressing
Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Daniel Ma, Yisen Wang
Spotlight
Mon 20:28 Fast Geometric Projections for Local Robustness Certification
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina Pasareanu
Spotlight
Mon 20:38 Information Laundering for Model Privacy
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
Spotlight
Mon 20:48 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Spotlight
Mon 20:58 HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark
Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin
Spotlight
Mon 21:36 Graph Convolution with Low-rank Learnable Local Filters
Xiuyuan Cheng, Zichen Miao, Qiang Qiu
Spotlight
Mon 21:46 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Spotlight
Mon 21:56 Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning
Dong Bok Lee, Dongchan Min, Seanie Lee, Sung Ju Hwang
Invited Talk
Tue 0:00 Geometric Deep Learning: the Erlangen Programme of ML
Michael Bronstein
Poster
Tue 1:00 Capturing Label Characteristics in VAEs
Tom W Joy, Sebastian Schmon, Philip Torr, Siddharth N, Tom Rainforth
Poster
Tue 1:00 Generalization in data-driven models of primary visual cortex
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Jagadish, Eric Wang, Edgar Walker, Santiago Cadena Cadena, Taliah Muhammad, Erick M Cobos, Andreas Tolias, Alexander S Ecker, Fabian Sinz
Poster
Tue 1:00 Activation-level uncertainty in deep neural networks
Pablo Morales-Alvarez, Daniel Hernández-Lobato, Rafael Molina, José Miguel Hernández Lobato
Poster
Tue 1:00 What they do when in doubt: a study of inductive biases in seq2seq learners
Kharitonov Eugene, Rahma Chaabouni
Poster
Tue 1:00 Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize
Nils Wandel, Michael Weinmann, Reinhard Klein
Poster
Tue 1:00 Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
Deunsol Yoon, Sunghoon Hong, Byung-Jun Lee, Kee-Eung Kim
Poster
Tue 1:00 A Universal Representation Transformer Layer for Few-Shot Image Classification
Lu Liu, Will Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle
Poster
Tue 1:00 Learning the Pareto Front with Hypernetworks
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik
Poster
Tue 1:00 GraphCodeBERT: Pre-training Code Representations with Data Flow
Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie LIU, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, Michele Tufano, Shao Kun Deng, Colin Clement, Dawn Drain, Neels Sundaresan, Jian Yin, Daxin Jiang, Ming Zhou
Poster
Tue 1:00 Efficient Certified Defenses Against Patch Attacks on Image Classifiers
Jan Hendrik Metzen, Maksym Yatsura
Poster
Tue 1:00 Generalized Multimodal ELBO
Thomas Sutter, Imant Daunhawer, Julia E Vogt
Poster
Tue 1:00 Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent
El Mahdi El Mhamdi, Rachid Guerraoui, Sébastien Rouault
Poster
Tue 1:00 BOIL: Towards Representation Change for Few-shot Learning
Jaehoon Oh, Hyungjun Yoo, ChangHwan Kim, Se-Young Yun
Poster
Tue 1:00 Hyperbolic Neural Networks++
Ryohei Shimizu, YUSUKE Mukuta, Tatsuya Harada
Poster
Tue 1:00 On Self-Supervised Image Representations for GAN Evaluation
Stanislav Morozov, Andrey Voynov, Artem Babenko
Poster
Tue 1:00 Calibration tests beyond classification
David Widmann, Fredrik Lindsten, Dave Zachariah
Poster
Tue 1:00 Accurate Learning of Graph Representations with Graph Multiset Pooling
Jinheon Baek, Minki Kang, Sung Ju Hwang
Poster
Tue 1:00 Class Normalization for (Continual)? Generalized Zero-Shot Learning
Ivan Skorokhodov, Mohamed Elhoseiny
Poster
Tue 1:00 Prediction and generalisation over directed actions by grid cells
Changmin Yu, Timothy Behrens, Neil Burgess
Poster
Tue 1:00 Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator
Max B Paulus, Chris Maddison, Andreas Krause
Poster
Tue 1:00 Contemplating Real-World Object Classification
Ali Borji
Poster
Tue 1:00 Coping with Label Shift via Distributionally Robust Optimisation
Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra
Poster
Tue 1:00 PDE-Driven Spatiotemporal Disentanglement
Jérémie DONA, Jean-Yves Franceschi, sylvain lamprier, patrick gallinari
Poster
Tue 1:00 Generalized Energy Based Models
Michael Arbel, Liang Zhou, Arthur Gretton
Poster
Tue 1:00 Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, Sanja Fidler
Poster
Tue 1:00 Multiscale Score Matching for Out-of-Distribution Detection
Ahsan Mahmood, Junier Oliva, Martin A Styner
Poster
Tue 1:00 not-MIWAE: Deep Generative Modelling with Missing not at Random Data
Niels Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
Poster
Tue 1:00 IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression
Rianne van den Berg, Alexey Gritsenko, Mostafa Dehghani, Casper Sønderby, Tim Salimans
Poster
Tue 1:00 A Distributional Approach to Controlled Text Generation
Muhammad Khalifa, Hady Elsahar, Marc Dymetman
Poster
Tue 1:00 Practical Real Time Recurrent Learning with a Sparse Approximation
Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves
Poster
Tue 1:00 Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples
Ziang Yan, Yiwen Guo, Jian Liang, Changshui Zhang
Poster
Tue 1:00 Learning Accurate Entropy Model with Global Reference for Image Compression
Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Li Hao, Rong Jin
Poster
Tue 1:00 Effective Abstract Reasoning with Dual-Contrast Network
Tao Zhuo, Mohan Kankanhalli
Poster
Tue 1:00 A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention
Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont, Julien Mairal
Poster
Tue 1:00 SkipW: Resource Adaptable RNN with Strict Upper Computational Limit
Tsiry MAYET, Anne Lambert, Pascal Le Guyadec, Francoise Le Bolzer, François Schnitzler
Poster
Tue 1:00 Bayesian Context Aggregation for Neural Processes
Michael Volpp, Fabian Flürenbrock, Lukas Grossberger, Christian Daniel, Gerhard Neumann
Poster
Tue 1:00 FedMix: Approximation of Mixup under Mean Augmented Federated Learning
Tehrim Yoon, Sumin Shin, Sung Ju Hwang, Eunho Yang
Poster
Tue 1:00 Do 2D GANs Know 3D Shape? Unsupervised 3D Shape Reconstruction from 2D Image GANs
Xingang Pan, Bo DAI, Ziwei Liu, Chen Change Loy, Ping Luo
Poster
Tue 1:00 MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering
Tsung Wei Tsai, Chongxuan Li, Jun Zhu
Poster
Tue 1:00 Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?
Balázs Kégl, Gabriel Hurtado, Albert Thomas
Poster
Tue 1:00 Complex Query Answering with Neural Link Predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez
Poster
Tue 1:00 Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling
Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M Buhmann
Poster
Tue 1:00 Risk-Averse Offline Reinforcement Learning
Núria Armengol Urpí, Sebastian Curi, Andreas Krause
Poster
Tue 1:00 Probing BERT in Hyperbolic Spaces
Boli Chen, Yao Fu, Guangwei Xu, Pengjun Xie, Chuanqi Tan, Mosha Chen, Liping Jing
Poster
Tue 1:00 Refining Deep Generative Models via Discriminator Gradient Flow
Abdul Fatir Ansari, Ming Liang Ang, Harold Soh
Poster
Tue 1:00 AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
Ke Sun, Zhanxing Zhu, Zhouchen Lin
Poster
Tue 1:00 Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing
Asish Ghoshal, Xilun Chen, Sonal Gupta, Luke Zettlemoyer, Yashar Mehdad
Poster
Tue 1:00 Prototypical Contrastive Learning of Unsupervised Representations
Junnan Li, Pan Zhou, Caiming Xiong, Steven Hoi
Poster
Tue 1:00 Lossless Compression of Structured Convolutional Models via Lifting
Gustav Sourek, Filip Zelezny, Ondrej Kuzelka
Poster
Tue 1:00 Disambiguating Symbolic Expressions in Informal Documents
Dennis Müller, Cezary Kaliszyk
Oral
Tue 3:00 End-to-end Adversarial Text-to-Speech
Jeff Donahue, Sander Dieleman, Mikolaj Binkowski, Erich Elsen, Karen Simonyan
Spotlight
Tue 3:15 Autoregressive Entity Retrieval
Nicola De Cao, Gautier Izacard, Sebastian Riedel, Fabio Petroni
Spotlight
Tue 3:25 Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking
Michael Schlichtkrull, Nicola De Cao, Ivan Titov
Spotlight
Tue 3:35 Expressive Power of Invariant and Equivariant Graph Neural Networks
Waïss Azizian, marc lelarge
Spotlight
Tue 3:45 Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
Pim De Haan, Maurice Weiler, Taco Cohen, Max Welling
Oral
Tue 4:08 Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator
Max B Paulus, Chris Maddison, Andreas Krause
Oral
Tue 4:23 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Spotlight
Tue 4:38 Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf
Spotlight
Tue 4:48 Noise against noise: stochastic label noise helps combat inherent label noise
Pengfei Chen, Guangyong Chen, Junjie Ye, jingwei zhao, Pheng-Ann Heng
Spotlight
Tue 5:18 Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize
Nils Wandel, Michael Weinmann, Reinhard Klein
Spotlight
Tue 5:38 Fidelity-based Deep Adiabatic Scheduling
Eli Ovits, Lior Wolf
Poster
Tue 9:00 VTNet: Visual Transformer Network for Object Goal Navigation
Heming Du, Xin Yu, Liang Zheng
Poster
Tue 9:00 Large Associative Memory Problem in Neurobiology and Machine Learning
Dmitry Krotov, John J Hopfield
Poster
Tue 9:00 On the Dynamics of Training Attention Models
Haoye Lu, Yongyi Mao, Amiya Nayak
Poster
Tue 9:00 Tent: Fully Test-Time Adaptation by Entropy Minimization
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno Olshausen, trevor darrell
Poster
Tue 9:00 Nearest Neighbor Machine Translation
Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis
Poster
Tue 9:00 SSD: A Unified Framework for Self-Supervised Outlier Detection
Vikash Sehwag, Mung Chiang, Prateek Mittal
Poster
Tue 9:00 Learning Parametrised Graph Shift Operators
George Dasoulas, Johannes Lutzeyer, Michalis Vazirgiannis
Poster
Tue 9:00 Support-set bottlenecks for video-text representation learning
Mandela Patrick, Po-Yao Huang, Yuki Asano, Florian Metze, Alexander G Hauptmann, Joao F. Henriques, Andrea Vedaldi
Poster
Tue 9:00 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Poster
Tue 9:00 Rethinking Attention with Performers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Richard Song, Georgiana-Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Q Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J Colwell, Adrian Weller
Poster
Tue 9:00 Mapping the Timescale Organization of Neural Language Models
Hsiang-Yun Sherry Chien, Jinhan Zhang, Christopher Honey
Poster
Tue 9:00 Learning Robust State Abstractions for Hidden-Parameter Block MDPs
Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau
Poster
Tue 9:00 Learning Neural Event Functions for Ordinary Differential Equations
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
Poster
Tue 9:00 Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández Lobato
Poster
Tue 9:00 C-Learning: Horizon-Aware Cumulative Accessibility Estimation
Panteha Naderian, Gabriel Loaiza-Ganem, Harry Braviner, Anthony Caterini, Jesse C Cresswell, Tong Li, Animesh Garg
Tue 9:00 How to shine in your technical presentation
Poster
Tue 9:00 DC3: A learning method for optimization with hard constraints
Priya Donti, David Rolnick, Zico Kolter
Poster
Tue 9:00 Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments
Daochen Zha, Wenye Ma, Lei Yuan, Xia Hu, Ji Liu
Poster
Tue 9:00 Learning a Latent Search Space for Routing Problems using Variational Autoencoders
André Hottung, Bhanu Bhandari, Kevin Tierney
Poster
Tue 9:00 DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues
Rishabh Joshi, Vidhisha Balachandran, Shikhar Vashishth, Alan Black, Yulia Tsvetkov
Poster
Tue 9:00 Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics
Yanchao Sun, Da Huo, Furong Huang
Poster
Tue 9:00 Interpreting Knowledge Graph Relation Representation from Word Embeddings
Carl Allen, Ivana Balazevic, Timothy Hospedales
Poster
Tue 9:00 FairBatch: Batch Selection for Model Fairness
Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
Poster
Tue 9:00 Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions
Yunwen Lei, Yiming Ying
Poster
Tue 9:00 UMEC: Unified model and embedding compression for efficient recommendation systems
Jiayi Shen, Haotao Wang, Shupeng Gui, Jianchao Tan, Zhangyang Wang, Ji Liu
Poster
Tue 9:00 Systematic generalisation with group invariant predictions
Faruk Ahmed, Yoshua Bengio, Harm van Seijen, Aaron Courville
Poster
Tue 9:00 Uncertainty Estimation in Autoregressive Structured Prediction
Andrey Malinin, Mark Gales
Poster
Tue 9:00 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Poster
Tue 9:00 Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
Poster
Tue 9:00 Ringing ReLUs: Harmonic Distortion Analysis of Nonlinear Feedforward Networks
Christian Ali Mehmeti-Göpel, David Hartmann, Michael Wand
Poster
Tue 9:00 Transformer protein language models are unsupervised structure learners
Roshan Rao, Joshua Meier, Tom Sercu, Sergey Ovchinnikov, Alexander Rives
Poster
Tue 9:00 On the Origin of Implicit Regularization in Stochastic Gradient Descent
Samuel Smith, Benoit Dherin, David Barrett, Soham De
Poster
Tue 9:00 Are wider nets better given the same number of parameters?
Anna Golubeva, Guy Gur-Ari, Behnam Neyshabur
Poster
Tue 9:00 Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning
Beliz Gunel, Jingfei Du, Alexis Conneau, Veselin Stoyanov
Poster
Tue 9:00 Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis
Bingchen Liu, Yizhe Zhu, Kunpeng Song, Ahmed Elgammal
Poster
Tue 9:00 VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat
Poster
Tue 9:00 Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics
Vinay Ramasesh, Ethan Dyer, Maithra Raghu
Poster
Tue 9:00 Uncertainty-aware Active Learning for Optimal Bayesian Classifier
Guang Zhao, Edward Dougherty, Byung-Jun Yoon, Francis Alexander, Xiaoning Qian
Poster
Tue 9:00 Statistical inference for individual fairness
Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
Poster
Tue 9:00 Fair Mixup: Fairness via Interpolation
Ching-Yao Chuang, Youssef Mroueh
Poster
Tue 9:00 Meta-learning Symmetries by Reparameterization
Allan Zhou, Tom Knowles, Chelsea Finn
Poster
Tue 9:00 Decoupling Global and Local Representations via Invertible Generative Flows
Xuezhe Ma, Xiang Kong, Shanghang Zhang, Eduard H Hovy
Poster
Tue 9:00 Self-Supervised Learning of Compressed Video Representations
Youngjae Yu, Sangho Lee, Gunhee Kim, Yale Song
Poster
Tue 9:00 Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J Townshend, Ron Dror
Poster
Tue 9:00 On the mapping between Hopfield networks and Restricted Boltzmann Machines
Matthew Smart, Anton Zilman
Poster
Tue 9:00 How Benign is Benign Overfitting ?
Amartya Sanyal, Puneet Dokania, Varun Kanade, Philip Torr
Poster
Tue 9:00 Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks
Thomas Bird, Friso Kingma, David Barber
Poster
Tue 9:00 Teaching with Commentaries
Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey Hinton
Poster
Tue 9:00 DINO: A Conditional Energy-Based GAN for Domain Translation
Konstantinos Vougioukas, Stavros Petridis, Maja Pantic
Poster
Tue 9:00 SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments
Glen Berseth, Daniel Geng, Coline M Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
Poster
Tue 9:00 Shape or Texture: Understanding Discriminative Features in CNNs
Md Amirul Islam, Matthew Kowal, Patrick Esser, Sen Jia, Björn Ommer, Kosta Derpanis, Neil Bruce
Poster
Tue 9:00 Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
Jingfeng Wu, Difan Zou, vladimir braverman, Quanquan Gu
Poster
Tue 9:00 Physics-aware, probabilistic model order reduction with guaranteed stability
Sebastian Kaltenbach, PS Koutsourelakis
Poster
Tue 9:00 Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman
Poster
Tue 9:00 Clairvoyance: A Pipeline Toolkit for Medical Time Series
Dan Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar
Poster
Tue 9:00 Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime
Andrea Agazzi, Jianfeng Lu
Poster
Tue 9:00 Tradeoffs in Data Augmentation: An Empirical Study
Rapha Gontijo Lopes, Sylvia Smullin, Ekin Cubuk, Ethan Dyer
Poster
Tue 9:00 Understanding Over-parameterization in Generative Adversarial Networks
Yogesh Balaji, Mohammadmahdi Sajedi, Neha Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi
Poster
Tue 9:00 Text Generation by Learning from Demonstrations
Richard Pang, He He
Oral
Tue 11:15 Learning Generalizable Visual Representations via Interactive Gameplay
Luca Weihs, Ani Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi
Spotlight
Tue 11:30 How Does Mixup Help With Robustness and Generalization?
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou
Oral
Tue 12:00 Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P Adams
Oral
Tue 12:15 Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, Sanja Fidler
Spotlight
Tue 12:50 Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J Townshend, Ron Dror
Oral
Tue 13:13 On the mapping between Hopfield networks and Restricted Boltzmann Machines
Matthew Smart, Anton Zilman
Spotlight
Tue 13:38 Long-tail learning via logit adjustment
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
Poster
Tue 17:00 Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
Thao Nguyen, Maithra Raghu, Simon Kornblith
Poster
Tue 17:00 Viewmaker Networks: Learning Views for Unsupervised Representation Learning
Alex Tamkin, Mike Wu, Noah Goodman
Poster
Tue 17:00 CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding
Yanru Qu, Dinghan Shen, Yelong Shen, Sandra Sajeev, Weizhu Chen, Jiawei Han
Poster
Tue 17:00 Diverse Video Generation using a Gaussian Process Trigger
Gaurav Shrivastava, Abhinav Shrivastava
Poster
Tue 17:00 CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks
Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei
Poster
Tue 17:00 A Temporal Kernel Approach for Deep Learning with Continuous-time Information
Da Xu, Chuanwei Ruan, evren korpeoglu, Sushant Kumar, kannan achan
Poster
Tue 17:00 How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
Dongkwan Kim, Alice Oh
Poster
Tue 17:00 Hierarchical Autoregressive Modeling for Neural Video Compression
Ruihan Yang, Yibo Yang, Joe Marino, Stephan Mandt
Poster
Tue 17:00 Individually Fair Rankings
Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun
Poster
Tue 17:00 Deep Equals Shallow for ReLU Networks in Kernel Regimes
Alberto Bietti, Francis Bach
Poster
Tue 17:00 Monotonic Kronecker-Factored Lattice
William Bakst, Nobuyuki Morioka, Erez Louidor
Poster
Tue 17:00 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
Poster
Tue 17:00 Contextual Dropout: An Efficient Sample-Dependent Dropout Module
XINJIE FAN, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou
Poster
Tue 17:00 Mirostat: A Neural Text Decoding Algorithm That Directly Controls Perplexity
Sourya Basu, Govardana Sachithanandam Ramachandran, Nitish Shirish Keskar, Lav R Varshney
Poster
Tue 17:00 Information Laundering for Model Privacy
Xinran Wang, Yu Xiang, Jun Gao, Jie Ding
Poster
Tue 17:00 Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
Haibo Yang, Minghong Fang, Jia Liu
Poster
Tue 17:00 Debiasing Concept-based Explanations with Causal Analysis
Taha Bahadori, David Heckerman
Poster
Tue 17:00 Concept Learners for Few-Shot Learning
Kaidi Cao, Maria Brbic, Jure Leskovec
Poster
Tue 17:00 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Poster
Tue 17:00 Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song
Poster
Tue 17:00 Discrete Graph Structure Learning for Forecasting Multiple Time Series
Chao Shang, Jie Chen, Jinbo Bi
Poster
Tue 17:00 Denoising Diffusion Implicit Models
Jiaming Song, Chenlin Meng, Stefano Ermon
Poster
Tue 17:00 BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration
Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, Hanjun Dai
Poster
Tue 17:00 Learning Safe Multi-agent Control with Decentralized Neural Barrier Certificates
Zengyi Qin, Kaiqing Zhang, chenyx Chen, Jingkai Chen, Chuchu Fan
Poster
Tue 17:00 Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
Michael Zhang, Tom Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, ziyu wang, Mohammad Norouzi
Poster
Tue 17:00 Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation
Peiye Zhuang, Sanmi Koyejo, Alex Schwing
Poster
Tue 17:00 Usable Information and Evolution of Optimal Representations During Training
Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan Kao
Poster
Tue 17:00 Linear Mode Connectivity in Multitask and Continual Learning
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Dilan Gorur, Razvan Pascanu, Hassan Ghasemzadeh
Poster
Tue 17:00 HalentNet: Multimodal Trajectory Forecasting with Hallucinative Intents
Deyao Zhu, Mohamed Zahran, Li Erran Li, Mohamed Elhoseiny
Poster
Tue 17:00 Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
Poster
Tue 17:00 FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning
Hong-You Chen, Wei-Lun Chao
Poster
Tue 17:00 Aligning AI With Shared Human Values
Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, Jacob Steinhardt
Poster
Tue 17:00 Discovering Non-monotonic Autoregressive Orderings with Variational Inference
Xuanlin Li, Brandon Trabucco, Dong Huk Park, Michael Luo, Sheng Shen, trevor darrell, Yang Gao
Poster
Tue 17:00 CcGAN: Continuous Conditional Generative Adversarial Networks for Image Generation
Xin Ding, Yongwei Wang, Zuheng Xu, William J Welch, Z. J Wang
Poster
Tue 17:00 Mathematical Reasoning via Self-supervised Skip-tree Training
Markus Rabe, Dennis Lee, Kshitij Bansal, Christian Szegedy
Poster
Tue 17:00 On Graph Neural Networks versus Graph-Augmented MLPs
Lei Chen, Zhengdao Chen, Joan Bruna
Poster
Tue 17:00 RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
Meng Qu, Junkun Chen, Louis-Pascal A Xhonneux, Yoshua Bengio, Jian Tang
Poster
Tue 17:00 Can a Fruit Fly Learn Word Embeddings?
Yuchen Liang, Chaitanya Ryali, Ben Hoover, Leopold Grinberg, Saket Navlakha, Mohammed J Zaki, Dmitry Krotov
Poster
Tue 17:00 Lipschitz Recurrent Neural Networks
N. Benjamin Erichson, Omri Azencot, Alejandro Queiruga, Liam Hodgkinson, Michael W Mahoney
Poster
Tue 17:00 DrNAS: Dirichlet Neural Architecture Search
Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh
Poster
Tue 17:00 Generalized Variational Continual Learning
Noel Loo, Siddharth Swaroop, Rich E Turner
Poster
Tue 17:00 Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning
Tsung-Wei Ke, Jyh-Jing Hwang, Stella Yu
Poster
Tue 17:00 Multi-resolution modeling of a discrete stochastic process identifies causes of cancer
Adam Yaari, Maxwell Sherman, Oliver C Priebe, Po-Ru Loh, Boris Katz, Andrei Barbu, Bonnie Berger
Poster
Tue 17:00 Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron Courville
Poster
Tue 17:00 A Hypergradient Approach to Robust Regression without Correspondence
Yujia Xie, Yixiu Mao, Simiao Zuo, Hongteng Xu, Xiaojing Ye, Tuo Zhao, Hongyuan Zha
Poster
Tue 17:00 Unsupervised Discovery of 3D Physical Objects
Yilun Du, Kevin A Smith, Tomer Ullman, Joshua B Tenenbaum, Jiajun Wu
Poster
Tue 17:00 Fourier Neural Operator for Parametric Partial Differential Equations
Zongyi Li, Nikola B Kovachki, Kamyar Azizzadenesheli, Burigede liu, Kaushik Bhattacharya, Andrew Stuart, Anima Anandkumar
Poster
Tue 17:00 CompOFA – Compound Once-For-All Networks for Faster Multi-Platform Deployment
Manas Sahni, Shreya Varshini, Alind Khare, Alexey Tumanov
Poster
Tue 17:00 Knowledge Distillation as Semiparametric Inference
Tri Dao, Govinda Kamath, Vasilis Syrgkanis, Lester Mackey
Poster
Tue 17:00 Attentional Constellation Nets for Few-Shot Learning
Weijian Xu, Yifan Xu, Huaijin Wang, Zhuowen Tu
Poster
Tue 17:00 Memory Optimization for Deep Networks
Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl
Poster
Tue 17:00 Generating Adversarial Computer Programs using Optimized Obfuscations
Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shiyu Chang, Quanfu Fan, Gaoyuan Zhang, Una-May O'Reilly
Poster
Tue 17:00 Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis
Zhipeng Bao, Yu-Xiong Wang, Martial Hebert
Poster
Tue 17:00 A Discriminative Gaussian Mixture Model with Sparsity
Hideaki Hayashi, Seiichi Uchida
Oral
Tue 19:00 Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
Brenden Petersen, Mikel Landajuela Larma, Terrell N Mundhenk, Claudio Santiago, Soo Kim, Joanne Kim
Spotlight
Tue 19:25 Orthogonalizing Convolutional Layers with the Cayley Transform
Asher Trockman, Zico Kolter
Spotlight
Tue 19:35 Model-Based Visual Planning with Self-Supervised Functional Distances
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Ben Eysenbach, Chelsea Finn, Sergey Levine
Oral
Tue 19:55 Global Convergence of Three-layer Neural Networks in the Mean Field Regime
Huy Tuan Pham, Phan-Minh Nguyen
Spotlight
Tue 20:30 Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
Spotlight
Tue 20:40 Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
Oral
Tue 21:03 Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song
Oral
Tue 21:18 MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training
Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan L Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Re
Spotlight
Tue 21:43 Memory Optimization for Deep Networks
Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl
Spotlight
Tue 21:53 Neural Topic Model via Optimal Transport
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray Buntine
Invited Talk
Wed 0:00 Perceiving the 3D World from Images and Video
Lourdes Agapito
Poster
Wed 1:00 BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
Yuhang Li, Ruihao Gong, Xu Tan, Yang Yang, Peng Hu, Qi Zhang, fengwei yu, Wei Wang, Shi Gu
Poster
Wed 1:00 Deep Learning meets Projective Clustering
Alaa Maalouf, Harry Lang, Daniela Rus, Dan Feldman
Poster
Wed 1:00 Gradient Origin Networks
Sam Bond-Taylor, Chris G Willcocks
Poster
Wed 1:00 Active Contrastive Learning of Audio-Visual Video Representations
Shuang Ma, Zhaoyang Zeng, Daniel McDuff, Yale Song
Poster
Wed 1:00 Disentangled Recurrent Wasserstein Autoencoder
Jun Han, Martin Min, Ligong Han, Li Erran Li, Xuan Zhang
Poster
Wed 1:00 Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models
Yuge Shi, Brooks Paige, Philip Torr, Siddharth N
Poster
Wed 1:00 No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks
Shyamgopal Karthik, Ameya Prabhu, Puneet Dokania, Vineet Gandhi
Poster
Wed 1:00 High-Capacity Expert Binary Networks
Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos
Poster
Wed 1:00 Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
Poster
Wed 1:00 Expressive Power of Invariant and Equivariant Graph Neural Networks
Waïss Azizian, marc lelarge
Poster
Wed 1:00 Geometry-aware Instance-reweighted Adversarial Training
Jingfeng Zhang, Jianing ZHU, Gang Niu, Bo Han, Masashi Sugiyama, Mohan Kankanhalli
Poster
Wed 1:00 Dance Revolution: Long-Term Dance Generation with Music via Curriculum Learning
Ruozi Huang, Huang Hu, Wei Wu, Kei Sawada, Mi Zhang, Daxin Jiang
Poster
Wed 1:00 Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu
Poster
Wed 1:00 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Poster
Wed 1:00 Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein
Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui
Poster
Wed 1:00 Neural networks with late-phase weights
Johannes von Oswald, Seijin Kobayashi, Joao Sacramento, Alexander Meulemans, Christian Henning, Benjamin F Grewe
Poster
Wed 1:00 Acting in Delayed Environments with Non-Stationary Markov Policies
Esther Derman, Gal Dalal, Shie Mannor
Poster
Wed 1:00 Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech
Yoonhyung Lee, Joongbo Shin, Kyomin Jung
Poster
Wed 1:00 IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning
Manli Zhang, Jianhong Zhang, Zhiwu Lu, Tao Xiang, Mingyu Ding, Songfang Huang
Poster
Wed 1:00 A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning
Samuel Horváth, Peter Richtarik
Poster
Wed 1:00 Neural Delay Differential Equations
Qunxi Zhu, Yao Guo, Wei Lin
Poster
Wed 1:00 Graph Edit Networks
Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara E Hammer
Poster
Wed 1:00 Learning Task Decomposition with Ordered Memory Policy Network
Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron Courville, Joshua B Tenenbaum, Chuang Gan
Poster
Wed 1:00 Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Yuan Yin, Vincent Le Guen, Jérémie DONA, Emmanuel d Bezenac, Ibrahim Ayed, Nicolas THOME, patrick gallinari
Poster
Wed 1:00 Identifying Physical Law of Hamiltonian Systems via Meta-Learning
Seungjun Lee, Haesang Yang, Woojae Seong
Poster
Wed 1:00 Reweighting Augmented Samples by Minimizing the Maximal Expected Loss
Mingyang Yi, LU HOU, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
Poster
Wed 1:00 Simple Spectral Graph Convolution
Hao Zhu, Piotr Koniusz
Poster
Wed 1:00 Auxiliary Task Update Decomposition: The Good, the Bad and the Neutral
Lucio Dery, Yann Dauphin, David Grangier
Poster
Wed 1:00 Degree-Quant: Quantization-Aware Training for Graph Neural Networks
Shyam Tailor, Javier Fernandez-Marques, Nic Lane
Poster
Wed 1:00 A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels
Leon Lang, Maurice Weiler
Poster
Wed 1:00 Long Range Arena : A Benchmark for Efficient Transformers
Yi Tay, Mostafa Dehghani, Samira Abnar, Yikang Shen, Dara Bahri, Philip Pham, Jinfeng Rao, Liu Yang, Sebastian Ruder, Donald Metzler
Poster
Wed 1:00 Differentiable Segmentation of Sequences
Erik Scharwächter, Jonathan Lennartz, Emmanuel Müller
Poster
Wed 1:00 Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels
Binxin Ru, Xingchen Wan, Xiaowen Dong, Michael Osborne
Poster
Wed 1:00 Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning
Alihan Hüyük, Dan Jarrett, Cem Tekin, Mihaela van der Schaar
Poster
Wed 1:00 Net-DNF: Effective Deep Modeling of Tabular Data
Liran Katzir, Gal Elidan, Ran El-Yaniv
Poster
Wed 1:00 A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
Sanghyun Hong, Yigitcan Kaya, Ionut-Vlad Modoranu, Tudor Dumitras
Poster
Wed 1:00 Communication in Multi-Agent Reinforcement Learning: Intention Sharing
WOOJUN KIM, Jongeui Park, Youngchul Sung
Poster
Wed 1:00 Knowledge distillation via softmax regression representation learning
Jing Yang, Brais Martinez, Adrian Bulat, Georgios Tzimiropoulos
Poster
Wed 1:00 Fidelity-based Deep Adiabatic Scheduling
Eli Ovits, Lior Wolf
Poster
Wed 1:00 FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization
Lanqing Li, Rui Yang, Dijun Luo
Poster
Wed 1:00 Separation and Concentration in Deep Networks
John Zarka, Florentin Guth, Stéphane Mallat
Poster
Wed 1:00 CoCon: A Self-Supervised Approach for Controlled Text Generation
Alvin Chan, Yew-Soon Ong, Bill Pung, Aston Zhang, Jie Fu
Poster
Wed 1:00 On Data-Augmentation and Consistency-Based Semi-Supervised Learning
Atin Ghosh, alexandre thiery
Poster
Wed 1:00 Learning Associative Inference Using Fast Weight Memory
Imanol Schlag, Tsendsuren Munkhdalai, Jürgen Schmidhuber
Poster
Wed 1:00 Learning from Demonstration with Weakly Supervised Disentanglement
Yordan Hristov, Subramanian Ramamoorthy
Poster
Wed 1:00 Self-supervised Adversarial Robustness for the Low-label, High-data Regime
Sven Gowal, Po-Sen Huang, Aaron v den, Timothy A Mann, Pushmeet Kohli
Poster
Wed 1:00 Neural gradients are near-lognormal: improved quantized and sparse training
Brian Chmiel, Liad Ben-Uri, Moran Shkolnik, Elad Hoffer, Ron Banner, Daniel Soudry
Poster
Wed 1:00 Improving Adversarial Robustness via Channel-wise Activation Suppressing
Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Daniel Ma, Yisen Wang
Poster
Wed 1:00 Bag of Tricks for Adversarial Training
Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu
Poster
Wed 1:00 Explainable Deep One-Class Classification
Philipp Liznerski, Lukas Ruff, Robert A Vandermeulen, Billy J Franks, Marius Kloft, Klaus R Muller
Poster
Wed 1:00 Neural ODE Processes
Alexander Norcliffe, Cristian Bodnar, Ben Day, Jacob Moss, Pietro Liò
Poster
Wed 1:00 Negative Data Augmentation
Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin, Stefano Ermon
Oral
Wed 3:15 Rethinking Attention with Performers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Richard Song, Georgiana-Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Q Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J Colwell, Adrian Weller
Oral
Wed 3:30 Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation
Biao Zhang, Ankur Bapna, Rico Sennrich, Orhan Firat
Spotlight
Wed 3:45 Support-set bottlenecks for video-text representation learning
Mandela Patrick, Po-Yao Huang, Yuki Asano, Florian Metze, Alexander G Hauptmann, Joao F. Henriques, Andrea Vedaldi
Oral
Wed 4:05 Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández Lobato
Spotlight
Wed 4:20 Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka, Takashi Kanemaru
Spotlight
Wed 4:40 Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
Spotlight
Wed 5:15 Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods
Taiji Suzuki, Akiyama Shunta
Spotlight
Wed 5:25 Tent: Fully Test-Time Adaptation by Entropy Minimization
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno Olshausen, trevor darrell
Spotlight
Wed 5:35 Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael U Gutmann, Aaron Courville, Zhanxing Zhu
Spotlight
Wed 5:45 Implicit Normalizing Flows
Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu
Wed 6:00 Panel discussion on model efficiency and quantization
Invited Talk
Wed 8:00 Is My Dataset Biased?
Kate Saenko
Poster
Wed 9:00 IsarStep: a Benchmark for High-level Mathematical Reasoning
Wenda Li, Lei Yu, Yuhuai Wu, Lawrence Paulson
Poster
Wed 9:00 A Gradient Flow Framework For Analyzing Network Pruning
Ekdeep Lubana, Robert Dick
Poster
Wed 9:00 Learning advanced mathematical computations from examples
François Charton, Amaury Hayat, Guillaume Lample
Poster
Wed 9:00 Early Stopping in Deep Networks: Double Descent and How to Eliminate it
Reinhard Heckel, Fatih Furkan Yilmaz
Poster
Wed 9:00 Anytime Sampling for Autoregressive Models via Ordered Autoencoding
Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon
Poster
Wed 9:00 Optimism in Reinforcement Learning with Generalized Linear Function Approximation
Yining Wang, Ruosong Wang, Simon Du, Akshay Krishnamurthy
Poster
Wed 9:00 OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
Poster
Wed 9:00 You Only Need Adversarial Supervision for Semantic Image Synthesis
Edgar Schoenfeld, Vadim Sushko, Dan Zhang, Juergen Gall, Bernt Schiele, Anna Khoreva
Poster
Wed 9:00 Neural Networks for Learning Counterfactual G-Invariances from Single Environments
S Chandra Mouli, Bruno Ribeiro
Poster
Wed 9:00 Training independent subnetworks for robust prediction
Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Dai, Dustin Tran
Poster
Wed 9:00 Generative Time-series Modeling with Fourier Flows
Ahmed Alaa, Alex Chan, Mihaela van der Schaar
Poster
Wed 9:00 Faster Binary Embeddings for Preserving Euclidean Distances
Jinjie Zhang, Rayan Saab
Poster
Wed 9:00 Learning Generalizable Visual Representations via Interactive Gameplay
Luca Weihs, Ani Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi
Poster
Wed 9:00 Growing Efficient Deep Networks by Structured Continuous Sparsification
Xin Yuan, Pedro Savarese, Michael Maire
Poster
Wed 9:00 Mastering Atari with Discrete World Models
Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, Jimmy Ba
Poster
Wed 9:00 DARTS-: Robustly Stepping out of Performance Collapse Without Indicators
Xiangxiang Chu, Victor Wang, Bo Zhang, Shun Lu, Xiaolin Wei, Junchi Yan
Poster
Wed 9:00 How Does Mixup Help With Robustness and Generalization?
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou
Poster
Wed 9:00 On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon, Eran Yahav
Poster
Wed 9:00 Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
Brenden Petersen, Mikel Landajuela Larma, Terrell N Mundhenk, Claudio Santiago, Soo Kim, Joanne Kim
Poster
Wed 9:00 RODE: Learning Roles to Decompose Multi-Agent Tasks
Tonghan Wang, Tarun Gupta, Anuj Mahajan, Bei Peng, Shimon Whiteson, Chongjie Zhang
Poster
Wed 9:00 Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning
Valerie Chen, Abhinav Gupta, Kenny Marino
Poster
Wed 9:00 HyperDynamics: Meta-Learning Object and Agent Dynamics with Hypernetworks
Zhou Xian, Shamit Lal, Hsiao-Yu Tung, Anthony Platanios, Katerina Fragkiadaki
Poster
Wed 9:00 Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Sergei Ivanov, Liudmila Prokhorenkova
Poster
Wed 9:00 HyperGrid Transformers: Towards A Single Model for Multiple Tasks
Yi Tay, Zhe Zhao, Dara Bahri, Donald Metzler, DA-CHENG Juan
Poster
Wed 9:00 Property Controllable Variational Autoencoder via Invertible Mutual Dependence
Xiaojie Guo, Yuanqi Du, Liang Zhao
Poster
Wed 9:00 Long-tail learning via logit adjustment
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
Poster
Wed 9:00 DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs
aayam shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
Poster
Wed 9:00 Neural Synthesis of Binaural Speech From Mono Audio
Alexander Richard, Dejan Markovic, Israel Gebru, Steven Krenn, Gladstone A Butler, Fernando Torre, Yaser Sheikh
Poster
Wed 9:00 Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
Paul Pu Liang, Manzil Zaheer, Yuan Wang, Amr Ahmed
Poster
Wed 9:00 Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning
Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan
Poster
Wed 9:00 TropEx: An Algorithm for Extracting Linear Terms in Deep Neural Networks
Martin Trimmel, Henning Petzka, Cristian Sminchisescu
Poster
Wed 9:00 More or Less: When and How to Build Convolutional Neural Network Ensembles
Abdul Wasay, Stratos Idreos
Poster
Wed 9:00 Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms
Maruan Al-Shedivat, Jennifer Gillenwater, Eric P Xing, Afshin Rostamizadeh
Poster
Wed 9:00 Unsupervised Audiovisual Synthesis via Exemplar Autoencoders
Kangle Deng, Aayush Bansal, Deva Ramanan
Poster
Wed 9:00 Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf
Poster
Wed 9:00 NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition
Abhinav Mehrotra, Alberto Gil Couto Pimentel Ramos, Sourav Bhattacharya, Łukasz Dudziak, Ravichander Vipperla, Thomas C Chau, Mohamed Abdelfattah, Samin Ishtiaq, Nic Lane
Poster
Wed 9:00 SEED: Self-supervised Distillation For Visual Representation
Jacob Zhiyuan Fang, Jianfeng Wang, Lijuan Wang, Lei Zhang, 'YZ' Yezhou Yang, Zicheng Liu
Poster
Wed 9:00 Theoretical bounds on estimation error for meta-learning
James Lucas, Mengye Ren, Irene Raissa KAMENI KAMENI, Toniann Pitassi, Richard Zemel
Poster
Wed 9:00 Evaluation of Neural Architectures Trained With Square Loss vs Cross-Entropy in Classification Tasks
Like Hui, Misha Belkin
Poster
Wed 9:00 Differentiable Trust Region Layers for Deep Reinforcement Learning
Fabian Otto, Philipp Becker, Vien A Ngo, Hanna Ziesche, Gerhard Neumann
Poster
Wed 9:00 Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
Poster
Wed 9:00 Pre-training Text-to-Text Transformers for Concept-centric Common Sense
Wangchunshu Zhou, Dong-Ho Lee, Ravi Kiran Selvam, Seyeon Lee, Xiang Ren
Poster
Wed 9:00 Self-supervised Visual Reinforcement Learning with Object-centric Representations
Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius
Poster
Wed 9:00 Exploring the Uncertainty Properties of Neural Networks’ Implicit Priors in the Infinite-Width Limit
Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington, Jasper Snoek
Poster
Wed 9:00 My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control
Vitaly Kurin, Maximilian Igl, Tim Rocktaeschel, Wendelin Boehmer, Shimon Whiteson
Poster
Wed 9:00 Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
Cassidy Laidlaw, ssingla Singla, Soheil Feizi
Poster
Wed 9:00 Few-Shot Bayesian Optimization with Deep Kernel Surrogates
Martin Wistuba, Josif Grabocka
Poster
Wed 9:00 Sharpness-aware Minimization for Efficiently Improving Generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, Behnam Neyshabur
Poster
Wed 9:00 PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds
Yujia Liu, Stefano D'Aronco, Konrad Schindler, Jan D Wegner
Poster
Wed 9:00 Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking
Michael Schlichtkrull, Nicola De Cao, Ivan Titov
Poster
Wed 9:00 Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Poster
Wed 9:00 Learning Mesh-Based Simulation with Graph Networks
Tobias Pfaff, Meire Fortunato, Alvaro Sanchez Gonzalez, Peter Battaglia
Poster
Wed 9:00 Average-case Acceleration for Bilinear Games and Normal Matrices
Carles Domingo i Enrich, Fabian Pedregosa, Damien Scieur
Poster
Wed 9:00 Benchmarks for Deep Off-Policy Evaluation
Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, ziyu wang, Alexander Novikov, Sherry Yang, Michael Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Paine
Poster
Wed 9:00 Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
Jonas Geiping, Liam H Fowl, Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
Poster
Wed 9:00 Sliced Kernelized Stein Discrepancy
Wenbo Gong, Yingzhen Li, José Miguel Hernández Lobato
Poster
Wed 9:00 Modeling the Second Player in Distributionally Robust Optimization
Paul Michel, Tatsunori Hashimoto, Graham Neubig
Poster
Wed 9:00 Orthogonalizing Convolutional Layers with the Cayley Transform
Asher Trockman, Zico Kolter
Poster
Wed 9:00 Learning Task-General Representations with Generative Neuro-Symbolic Modeling
Reuben Feinman, Brenden Lake
Oral
Wed 11:30 Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang, Rowan T McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
Oral
Wed 11:45 Evolving Reinforcement Learning Algorithms
John Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V Le, Sergey Levine, Honglak Lee, Aleksandra Faust
Spotlight
Wed 12:00 Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
Denis Yarats, Ilya Kostrikov, Rob Fergus
Oral
Wed 12:23 Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Spotlight
Wed 12:38 Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy
Akinori Ebihara, Taiki Miyagawa, Kazuyuki Sakurai, Hitoshi Imaoka
Spotlight
Wed 12:48 LambdaNetworks: Modeling long-range Interactions without Attention
Irwan Bello
Spotlight
Wed 12:58 Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
Spotlight
Wed 13:28 VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat
Spotlight
Wed 13:38 Dynamic Tensor Rematerialization
Marisa Kirisame, Steven S. Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared G Roesch, Tianqi Chen, Zachary Tatlock
Spotlight
Wed 13:48 A Gradient Flow Framework For Analyzing Network Pruning
Ekdeep Lubana, Robert Dick
Spotlight
Wed 13:58 Differentially Private Learning Needs Better Features (or Much More Data)
Florian Tramer, Dan Boneh
Expo Talk Panel
Wed 14:00 Live Panel - Academics@ Presents: Representation Learning at Amazon
Zahra Matson
Oral
Wed 16:00 Neural Synthesis of Binaural Speech From Mono Audio
Alexander Richard, Dejan Markovic, Israel Gebru, Steven Krenn, Gladstone A Butler, Fernando Torre, Yaser Sheikh
Oral
Wed 16:30 Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song, Jascha Sohl-Dickstein, Durk Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
Spotlight
Wed 16:45 Learning Mesh-Based Simulation with Graph Networks
Tobias Pfaff, Meire Fortunato, Alvaro Sanchez Gonzalez, Peter Battaglia
Poster
Wed 17:00 Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters
Aston Zhang, Yi Tay, Shuai Zhang, Alvin Chan, Anh Tuan Luu, Siu Hui, Jie Fu
Poster
Wed 17:00 Generating Furry Cars: Disentangling Object Shape and Appearance across Multiple Domains
Utkarsh Ojha, Krishna Kumar Singh, Yong Jae Lee
Poster
Wed 17:00 A Geometric Analysis of Deep Generative Image Models and Its Applications
Binxu Wang, Carlos Ponce
Poster
Wed 17:00 GANs Can Play Lottery Tickets Too
Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen
Poster
Wed 17:00 Estimating Lipschitz constants of monotone deep equilibrium models
Chirag Pabbaraju, Ezra Winston, Zico Kolter
Poster
Wed 17:00 Estimating informativeness of samples with Smooth Unique Information
Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Poster
Wed 17:00 NBDT: Neural-Backed Decision Tree
Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Suzanne Petryk, Sarah A Bargal, Joseph E Gonzalez
Poster
Wed 17:00 Meta Back-Translation
Hieu Pham, Xinyi Wang, Yiming Yang, Graham Neubig
Poster
Wed 17:00 Task-Agnostic Morphology Evolution
Donald Hejna III, Pieter Abbeel, Lerrel Pinto
Poster
Wed 17:00 CPR: Classifier-Projection Regularization for Continual Learning
Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flavio Calmon, Taesup Moon
Poster
Wed 17:00 Control-Aware Representations for Model-based Reinforcement Learning
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
Poster
Wed 17:00 Is Attention Better Than Matrix Decomposition?
Zhengyang Geng, Meng-Hao Guo, Hongxu Chen, Xia Li, Ke Wei, Zhouchen Lin
Poster
Wed 17:00 Empirical or Invariant Risk Minimization? A Sample Complexity Perspective
Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R Varshney
Poster
Wed 17:00 gradSim: Differentiable simulation for system identification and visuomotor control
Krishna Murthy Jatavallabhula, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini, Martin Weiss, Breandan Considine, Jérôme Parent-Lévesque, Kevin Xie, Kenny Erleben, Liam Paull, Florian Shkurti, Derek Nowrouzezahrai, Sanja Fidler
Poster
Wed 17:00 Evaluations and Methods for Explanation through Robustness Analysis
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep K Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
Poster
Wed 17:00 In Search of Lost Domain Generalization
Ishaan Gulrajani, David Lopez-Paz
Poster
Wed 17:00 Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
Benedikt Boecking, Willie Neiswanger, Eric P Xing, Artur Dubrawski
Poster
Wed 17:00 Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation
Jungo Kasai, Nikolaos Pappas, Hao Peng, James Cross, Noah Smith
Poster
Wed 17:00 Learning to Generate 3D Shapes with Generative Cellular Automata
Dongsu Zhang, Changwoon Choi, Jeonghwan Kim, Young Min Kim
Poster
Wed 17:00 PolarNet: Learning to Optimize Polar Keypoints for Keypoint Based Object Detection
xwwu xiongwei, Doyen Sahoo, Steven HOI
Poster
Wed 17:00 Robust Overfitting may be mitigated by properly learned smoothening
Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang
Poster
Wed 17:00 Measuring Massive Multitask Language Understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, Jacob Steinhardt
Poster
Wed 17:00 Learning Manifold Patch-Based Representations of Man-Made Shapes
Dmitriy Smirnov, Mikhail Bessmeltsev, Justin Solomon
Poster
Wed 17:00 Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs
Zhen Han, Peng Chen, Yunpu Ma, Volker Tresp
Poster
Wed 17:00 In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang
Poster
Wed 17:00 Simple Augmentation Goes a Long Way: ADRL for DNN Quantization
Lin Ning, Guoyang Chen, Weifeng Zhang, Xipeng Shen
Poster
Wed 17:00 AdaSpeech: Adaptive Text to Speech for Custom Voice
Mingjian Chen, Xu Tan, Bohan Li, Eric Liu, Tao Qin, sheng zhao, Tie-Yan Liu
Poster
Wed 17:00 Influence Functions in Deep Learning Are Fragile
Samyadeep Basu, Phil Pope, Soheil Feizi
Poster
Wed 17:00 ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
Mohit Shridhar, Eric Yuan, Marc-Alexandre Cote, Yonatan Bisk, Adam Trischler, Matthew Hausknecht
Poster
Wed 17:00 Economic Hyperparameter Optimization With Blended Search Strategy
Chi Wang, Qingyun Wu, Silu Huang, Amin Saied
Poster
Wed 17:00 AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly
Yuchen Jin, Tianyi Zhou, Liangyu Zhao, Yibo Zhu, Chuanxiong Guo, Marco Canini, Arvind Krishnamurthy
Poster
Wed 17:00 Evolving Reinforcement Learning Algorithms
John Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V Le, Sergey Levine, Honglak Lee, Aleksandra Faust
Poster
Wed 17:00 A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks
Renjie Liao, Raquel Urtasun, Richard Zemel
Poster
Wed 17:00 BERTology Meets Biology: Interpreting Attention in Protein Language Models
Jesse Vig, Ali Madani, Lav R Varshney, Caiming Xiong, Richard Socher, Nazneen Rajani
Poster
Wed 17:00 Adaptive Universal Generalized PageRank Graph Neural Network
Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic
Poster
Wed 17:00 Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
Mrigank Raman, Aaron Chan, Siddhant Agarwal, PeiFeng Wang, Hansen Wang, Sungchul Kim, Ryan Rossi, Handong Zhao, Nedim Lipka, Xiang Ren
Poster
Wed 17:00 Learning Long-term Visual Dynamics with Region Proposal Interaction Networks
Haozhi Qi, Xiaolong Wang, Deepak Pathak, Yi Ma, Jitendra Malik
Poster
Wed 17:00 Beyond Categorical Label Representations for Image Classification
Boyuan Chen, Yu Li, Sunand Raghupathi, Hod Lipson
Poster
Wed 17:00 CoCo: Controllable Counterfactuals for Evaluating Dialogue State Trackers
Shiyang Li, Semih Yavuz, Kazuma Hashimoto, Jia Li, Tong Niu, Nazneen Rajani, Xifeng Yan, Yingbo Zhou, Caiming Xiong
Poster
Wed 17:00 Revisiting Dynamic Convolution via Matrix Decomposition
Yunsheng Li, Yinpeng Chen, Xiyang Dai, mengchen liu, Dongdong Chen, Ye Yu, Lu Yuan, Zicheng Liu, Mei Chen, Nuno Vasconcelos
Poster
Wed 17:00 Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu
Poster
Wed 17:00 Better Fine-Tuning by Reducing Representational Collapse
Armen Aghajanyan, Akshat Shrivastava, Anchit Gupta, Naman Goyal, Luke Zettlemoyer, Sonal Gupta
Poster
Wed 17:00 Learning and Evaluating Representations for Deep One-Class Classification
Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
Poster
Wed 17:00 Individually Fair Gradient Boosting
Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
Poster
Wed 17:00 Model-Based Visual Planning with Self-Supervised Functional Distances
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Ben Eysenbach, Chelsea Finn, Sergey Levine
Poster
Wed 17:00 AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition
Yue Meng, Rameswar Panda, Chung-Ching Lin, Prasanna Sattigeri, Leonid Karlinsky, Kate Saenko, Aude Oliva, Rogerio Feris
Poster
Wed 17:00 Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System
Jianhong Wang, Yuan Zhang, Tae-Kyun Kim, Yunjie Gu
Poster
Wed 17:00 DiffWave: A Versatile Diffusion Model for Audio Synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, Bryan Catanzaro
Poster
Wed 17:00 Evaluating the Disentanglement of Deep Generative Models through Manifold Topology
Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Ng, Gunnar E Carlsson, Stefano Ermon
Poster
Wed 17:00 Learning with Feature-Dependent Label Noise: A Progressive Approach
Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen
Poster
Wed 17:00 Graph-Based Continual Learning
Binh Tang, David S Matteson
Poster
Wed 17:00 Improved Autoregressive Modeling with Distribution Smoothing
Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon
Poster
Wed 17:00 Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition
Yangming Li, lemao liu, Shuming Shi
Poster
Wed 17:00 Wandering within a world: Online contextualized few-shot learning
Mengye Ren, Michael L Iuzzolino, Mike Mozer, Richard Zemel
Poster
Wed 17:00 Protecting DNNs from Theft using an Ensemble of Diverse Models
Sanjay Kariyappa, Atul Prakash, Moinuddin K Qureshi
Oral
Wed 19:00 Improved Autoregressive Modeling with Distribution Smoothing
Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon
Spotlight
Wed 19:25 Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Shengyu Zhao, Jonathan Cui, Yilun Sheng, Yue Dong, Xiao Liang, Eric Chang, Yan Xu
Oral
Wed 19:55 Deformable DETR: Deformable Transformers for End-to-End Object Detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai
Wed 20:00 ML and Language (#1)
Spotlight
Wed 20:10 Graph-Based Continual Learning
Binh Tang, David S Matteson
Spotlight
Wed 20:20 Understanding the role of importance weighting for deep learning
Da Xu, Yuting Ye, Chuanwei Ruan
Spotlight
Wed 20:30 Towards Robustness Against Natural Language Word Substitutions
Xinshuai Dong, Anh Tuan Luu, Rongrong Ji, Hong Liu
Spotlight
Wed 20:40 Undistillable: Making A Nasty Teacher That CANNOT teach students
Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang
Spotlight
Wed 20:50 CPT: Efficient Deep Neural Network Training via Cyclic Precision
Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin
Spotlight
Wed 21:25 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang, trevor darrell
Oral
Thu 0:00 Rethinking Architecture Selection in Differentiable NAS
Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
Oral
Thu 0:15 Complex Query Answering with Neural Link Predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez
Spotlight
Thu 0:45 Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters
Aston Zhang, Yi Tay, Shuai Zhang, Alvin Chan, Anh Tuan Luu, Siu Hui, Jie Fu
Poster
Thu 1:00 Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel
Poster
Thu 1:00 Free Lunch for Few-shot Learning: Distribution Calibration
Shuo Yang, Lu Liu, Min Xu
Poster
Thu 1:00 Learning Neural Generative Dynamics for Molecular Conformation Generation
Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang
Poster
Thu 1:00 Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models
Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
Poster
Thu 1:00 Interpretable Models for Granger Causality Using Self-explaining Neural Networks
Ričards Marcinkevičs, Julia E Vogt
Poster
Thu 1:00 An Unsupervised Deep Learning Approach for Real-World Image Denoising
Dihan Zheng, Sia Huat Tan, Xiaowen Zhang, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao
Poster
Thu 1:00 Learning continuous-time PDEs from sparse data with graph neural networks
Valerii Iakovlev, Markus Heinonen, Harri Lähdesmäki
Poster
Thu 1:00 Deformable DETR: Deformable Transformers for End-to-End Object Detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai
Poster
Thu 1:00 Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues
(Henry) Hung Le, Nancy F Chen, Steven Hoi
Poster
Thu 1:00 Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory
Jason Ramapuram, Yan Wu, Alexandros Kalousis
Poster
Thu 1:00 Contrastive Divergence Learning is a Time Reversal Adversarial Game
Omer Yair, Tomer Michaeli
Poster
Thu 1:00 Learning What To Do by Simulating the Past
David Lindner, Rohin Shah, Pieter Abbeel, Anca Dragan
Poster
Thu 1:00 Counterfactual Generative Networks
Axel Sauer, Andreas Geiger
Poster
Thu 1:00 IOT: Instance-wise Layer Reordering for Transformer Structures
Jinhua Zhu, Lijun Wu, Yingce Xia, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu
Poster
Thu 1:00 Private Image Reconstruction from System Side Channels Using Generative Models
Yuanyuan Yuan, Shuai Wang, Junping Zhang
Poster
Thu 1:00 AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
Byeongho Heo, Sanghyuk Chun, Seong Joon Oh, Dongyoon Han, Sangdoo Yun, Gyuwan Kim, Youngjung Uh, Jung-Woo Ha
Poster
Thu 1:00 Incremental few-shot learning via vector quantization in deep embedded space
Kuilin Chen, Chi-Guhn Lee
Poster
Thu 1:00 Colorization Transformer
Manoj Kumar, Dirk Weissenborn, Nal Kalchbrenner
Poster
Thu 1:00 Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
Poster
Thu 1:00 Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search
Peidong Liu, Gengwei Zhang, Bochao Wang, Hang Xu, Xiaodan Liang, Yong Jiang, Zhenguo Li
Poster
Thu 1:00 R-GAP: Recursive Gradient Attack on Privacy
Junyi Zhu, Matthew Blaschko
Poster
Thu 1:00 GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, Zhifeng Chen
Poster
Thu 1:00 Latent Convergent Cross Mapping
Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau
Poster
Thu 1:00 Distilling Knowledge from Reader to Retriever for Question Answering
Gautier Izacard, Edouard Grave
Poster
Thu 1:00 Go with the flow: Adaptive control for Neural ODEs
Mathieu Chalvidal, Matthew Ricci, Rufin VanRullen, Thomas Serre
Poster
Thu 1:00 ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations
Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak Gupta
Poster
Thu 1:00 Conditional Generative Modeling via Learning the Latent Space
Sameera Ramasinghe, Kanchana Ranasinghe, Salman Khan, Nick Barnes, Stephen Gould
Poster
Thu 1:00 Contrastive Learning with Adversarial Perturbations for Conditional Text Generation
Seanie Lee, Dong Bok Lee, Sung Ju Hwang
Poster
Thu 1:00 Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kin-Ho Lam, Alan Fern
Poster
Thu 1:00 Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka, Takashi Kanemaru
Poster
Thu 1:00 Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning
Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien
Poster
Thu 1:00 Sparse Quantized Spectral Clustering
Zhenyu Liao, Romain Couillet, Michael W Mahoney
Poster
Thu 1:00 Categorical Normalizing Flows via Continuous Transformations
Phillip Lippe, Stratis Gavves
Poster
Thu 1:00 Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks
Jan Schuchardt, Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann
Poster
Thu 1:00 Efficient Generalized Spherical CNNs
Oliver Cobb, Christopher Wallis, Augustine Mavor-Parker, Augustin Marignier, Matthew Price, Mayeul d'Avezac, Jason McEwen
Poster
Thu 1:00 Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction
Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong
Poster
Thu 1:00 Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design
Xiufeng Yang, Tanuj Aasawat, Kazuki Yoshizoe
Poster
Thu 1:00 Understanding the effects of data parallelism and sparsity on neural network training
Namhoon Lee, Thalaiyasingam Ajanthan, Philip Torr, Martin Jaggi
Poster
Thu 1:00 Retrieval-Augmented Generation for Code Summarization via Hybrid GNN
Shangqing Liu, Yu Chen, Xiaofei Xie, Siow Jing Kai, Yang Liu
Poster
Thu 1:00 Hopfield Networks is All You Need
Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David Kreil, Michael K Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter
Poster
Thu 1:00 Representation Balancing Offline Model-based Reinforcement Learning
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Poster
Thu 1:00 Neural Topic Model via Optimal Transport
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray Buntine
Poster
Thu 1:00 Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks
Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li
Poster
Thu 1:00 Efficient Inference of Flexible Interaction in Spiking-neuron Networks
Feng Zhou, Yixuan Zhang, Jun Zhu
Poster
Thu 1:00 Certify or Predict: Boosting Certified Robustness with Compositional Architectures
Mark Niklas Mueller, Mislav Balunovic, Martin Vechev
Poster
Thu 1:00 Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
Shikuang Deng, Shi Gu
Poster
Thu 1:00 Autoregressive Entity Retrieval
Nicola De Cao, Gautier Izacard, Sebastian Riedel, Fabio Petroni
Poster
Thu 1:00 Learnable Embedding sizes for Recommender Systems
Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, Yong Li
Spotlight
Thu 3:15 Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
Deunsol Yoon, Sunghoon Hong, Byung-Jun Lee, Kee-Eung Kim
Spotlight
Thu 3:25 UPDeT: Universal Multi-agent RL via Policy Decoupling with Transformers
Siyi Hu, Fengda Zhu, Xiaojun Chang, Xiaodan Liang
Spotlight
Thu 3:35 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Oral
Thu 4:20 Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Yuan Yin, Vincent Le Guen, Jérémie DONA, Emmanuel d Bezenac, Ibrahim Ayed, Nicolas THOME, patrick gallinari
Spotlight
Thu 4:35 Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang, Daniel Ma, Sarah Erfani, James Bailey, Yisen Wang
Spotlight
Thu 4:45 Self-supervised Visual Reinforcement Learning with Object-centric Representations
Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius